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From Fitting Participation to Forging Relationships: The Art of Participatory ML

Published 11 Mar 2024 in cs.HC and cs.CY | (2403.06431v1)

Abstract: Participatory ML encourages the inclusion of end users and people affected by ML systems in design and development processes. We interviewed 18 participation brokers -- individuals who facilitate such inclusion and transform the products of participants' labour into inputs for an ML artefact or system -- across a range of organisational settings and project locations. Our findings demonstrate the inherent challenges of integrating messy contextual information generated through participation with the structured data formats required by ML workflows and the uneven power dynamics in project contexts. We advocate for evolution in the role of brokers to more equitably balance value generated in Participatory ML projects for design and development teams with value created for participants. To move beyond `fitting' participation to existing processes and empower participants to envision alternative futures through ML, brokers must become educators and advocates for end users, while attending to frustration and dissent from indirect stakeholders.

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References (82)
  1. Contestable Camera Cars: A Speculative Design Exploration of Public AI That Is Open and Responsive to Dispute. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (Hamburg, Germany) (CHI '23, Article 8). Association for Computing Machinery, New York, NY, USA, 1–16.
  2. Contestable AI by Design: Towards a Framework. Minds & Machines (Aug. 2022), 1–27. https://doi.org/10.1007/s11023-022-09611-z
  3. Sherry R Arnstein. 1969. A Ladder Of Citizen Participation. Journal of the American Institute of Planners 35, 4 (July 1969), 216–224.
  4. Reimagining participatory design. Interactions 26, 1 (Dec. 2018), 26–32.
  5. Ruha Benjamin. 2019. Race After Technology: Abolitionist Tools for the New Jim Code. Polity Press, Cambridge, UK.
  6. Participatory AI for humanitarian innovation: a briefing paper. Technical Report. Nesta. https://www.nesta.org.uk/report/participatory-ai-humanitarian-innovation-briefing-paper/
  7. Power to the People? Opportunities and Challenges for Participatory AI. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 6). Association for Computing Machinery, New York, NY, USA, 1–8.
  8. Participatory Design and ``Democratizing Innovation''. In Proceedings of the 11th Biennial Participatory Design Conference (Sydney, Australia) (PDC '10). Association for Computing Machinery, New York, NY, USA, 41–50.
  9. Susanne Bødker. 2006. When second wave HCI meets third wave challenges. In Proceedings of the 4th Nordic Conference on Human-Computer Interaction: Changing Roles (Oslo, Norway) (NordiCHI '06). Association for Computing Machinery, New York, NY, USA, 1–8.
  10. Susanne Bødker and Morten Kyng. 2018. Participatory Design That Matters—Facing the Big Issues. ACM Transactions on Computer-Human Interaction 25, 1 (Feb. 2018), 1–31.
  11. Man Is to Computer Programmer as Woman Is to Homemaker? Debiasing Word Embeddings. In Proceedings of the 30th International Conference on Neural Information Processing Systems (NIPS'16). Curran Associates Inc., Red Hook, NY, USA, 4356–4364.
  12. Envisioning Communities: A Participatory Approach towards AI for Social Good. In Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society (AIES '21). Association for Computing Machinery, New York, NY, USA, 425–436.
  13. Geoffrey C Bowker and Susan Leigh Star. 2000. Sorting Things Out: Classification and Its Consequences. MIT Press, Cambridge, MA, USA.
  14. Tone Bratteteig and Ina Wagner. 2014. Disentangling Participation: Power and Decision-making in Participatory Design. Springer, Switzerland.
  15. Virginia Braun and Victoria Clarke. 2006. Using Thematic Analysis in Psychology. Qualitative Research in Psychology. 3, 2 (2006), 77–101.
  16. Virginia Braun and Victoria Clarke. 2019. Reflecting on reflexive thematic analysis. Qualitative Research in Sport, Exercise and Health 11, 4 (Aug. 2019), 589–597.
  17. Virginia Braun and Victoria Clarke. 2020. One Size Fits All? What Counts as Quality Practice in (Reflexive) Thematic Analysis? Qualitative Research in Psychology 18, 3 (Aug. 2020), 1–25.
  18. Joy Buolamwini and Timnit Gebru. 2018. Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification. In Proceedings of the 1st Conference on Fairness, Accountability and Transparency (Proceedings of Machine Learning Research, Vol. 81), Sorelle A Friedler and Christo Wilson (Eds.). PMLR, New York, NY, USA, 77–91.
  19. David Byrne. 2022. A worked example of Braun and Clarke's approach to reflexive thematic analysis. Quality & Quantity 56, 3 (June 2022), 1391–1412.
  20. Relating Action to Activism: Theoretical and Methodological Reflections. In Participatory Action Research Approaches and Methods: Connecting People, Participation and Place, Sara Kindon, Rachel Pain, and Mike Kesby (Eds.). Routledge, London, UK, 216–222. https://play.google.com/store/books/details?id=daKkkt0NiPQC
  21. Soliciting Stakeholders' Fairness Notions in Child Maltreatment Predictive Systems. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, New York, NY, USA.
  22. Accountability in an Algorithmic Society: Relationality, Responsibility, and Robustness in Machine Learning. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 864–876.
  23. A Systematic Review and Thematic Analysis of Community-Collaborative Approaches to Computing Research. In CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 73). Association for Computing Machinery, New York, NY, USA, 1–18.
  24. Power and Public Participation in AI. In Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (Boston, MA, USA) (EAAMO '23, Article 8). Association for Computing Machinery, New York, NY, USA, 1–13. https://doi.org/10.1145/3617694.3623228
  25. Stakeholder Participation in AI: Beyond ``Add Diverse Stakeholders and Stir''. arXiv:2111.01122 [cs.AI]
  26. The Participatory Turn in AI Design: Theoretical Foundations and the Current State of Practice. In Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (Boston, MA, USA) (EAAMO '23, Article 37). Association for Computing Machinery, New York, NY, USA, 1–23. https://doi.org/10.1145/3617694.3623261
  27. Understanding Practices, Challenges, and Opportunities for User-Engaged Algorithm Auditing in Industry Practice. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (Hamburg, Germany) (CHI '23, Article 377). Association for Computing Machinery, New York, NY, USA, 1–18.
  28. Catherine D'Ignazio and Lauren F Klein. 2020. Data Feminism. The MIT Press, Cambridge, MA, USA.
  29. Communities: Participatory Design for, with and by Communities. In Routledge International Handbook of Participatory Design, Jesper Simonsen and Toni Robertson (Eds.). Taylor & Francis Group, London, UK.
  30. Hard Choices in Artificial Intelligence. Artificial Intelligence 300 (2021), 103555.
  31. Oxford Handbook of Ethics of AI. Oxford University Press, Oxford, UK.
  32. Human Rights and Technology Final Report. Technical Report. Australian Human Rights Commission, Sydney.
  33. From Preference Elicitation to Participatory ML: A Critical Survey & Guidelines for Future Research. In Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society (Montréal , QC, Canada) (AIES '23). Association for Computing Machinery, New York, NY, USA, 38–48. https://doi.org/10.1145/3600211.3604661
  34. Batya Friedman. 1996. Value-Sensitive Design. Interactions 3, 6 (Dec. 1996), 16–23.
  35. Batya Friedman and David G Hendry. 2019. Value Sensitive Design: Shaping Technology with Moral Imagination. The MIT Press, Cambridge, MA, USA.
  36. Ben Gansky and Sean McDonald. 2022. CounterFAccTual: How FAccT Undermines Its Organizing Principles. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1982–1992.
  37. Clifford Geertz. 1973. Thick Description: Toward an Interpretive Theory of Culture. In The Interpretation of Cultures. Basic Books, New York, NY, USA, 41–51.
  38. Better, Nicer, Clearer, Fairer: A Critical Assessment of the Movement for Ethical Artificial Intelligence and Machine Learning. In Proceedings of the 52nd Hawai`i International Conference on System Sciences. IEEE Computer Society Press, Honolulu, Hawai`i, USA, 2122–2131. Gregory (2003) Judith Gregory. 2003. Scandinavian approaches to participatory design. International Journal of Engineering Education 19, 1 (2003), 62–74. Groves et al. (2023) Lara Groves, Aidan Peppin, Andrew Strait, and Jenny Brennan. 2023. Going public: the role of public participation approaches in commercial AI labs. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1162–1173. Halfaker and Geiger (2020) Aaron Halfaker and R Stuart Geiger. 2020. ORES: Lowering Barriers with Participatory Machine Learning in Wikipedia. Proceedings of the ACM on Human-Computer Interaction 4, CSCW2 (Oct. 2020), 1–37. Hayes (2011) Gillian R Hayes. 2011. The Relationship of Action Research to Human-Computer Interaction. ACM Transactions on Computer-Human Interaction 18, 3 (Aug. 2011), 1–20. Hoffmann (2019) Anna Lauren Hoffmann. 2019. Where fairness fails: data, algorithms, and the limits of antidiscrimination discourse. Information, Communication & Society 22, 7 (June 2019), 900–915. Hu et al. (2019) Xianhong Hu, Bhanu Neupane, Lucia Flores Echaiz, Prateek Sibal, and Macarena Rivera Lam. 2019. Steering AI and Advanced ICTs for Knowledge Societies. United Nations Educational, Scientific and Cultural Organization (UNESCO), Paris, France. Hutchinson et al. (2020) Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Judith Gregory. 2003. Scandinavian approaches to participatory design. International Journal of Engineering Education 19, 1 (2003), 62–74. Groves et al. (2023) Lara Groves, Aidan Peppin, Andrew Strait, and Jenny Brennan. 2023. Going public: the role of public participation approaches in commercial AI labs. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1162–1173. Halfaker and Geiger (2020) Aaron Halfaker and R Stuart Geiger. 2020. ORES: Lowering Barriers with Participatory Machine Learning in Wikipedia. Proceedings of the ACM on Human-Computer Interaction 4, CSCW2 (Oct. 2020), 1–37. Hayes (2011) Gillian R Hayes. 2011. The Relationship of Action Research to Human-Computer Interaction. ACM Transactions on Computer-Human Interaction 18, 3 (Aug. 2011), 1–20. Hoffmann (2019) Anna Lauren Hoffmann. 2019. Where fairness fails: data, algorithms, and the limits of antidiscrimination discourse. Information, Communication & Society 22, 7 (June 2019), 900–915. Hu et al. (2019) Xianhong Hu, Bhanu Neupane, Lucia Flores Echaiz, Prateek Sibal, and Macarena Rivera Lam. 2019. Steering AI and Advanced ICTs for Knowledge Societies. United Nations Educational, Scientific and Cultural Organization (UNESCO), Paris, France. Hutchinson et al. (2020) Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lara Groves, Aidan Peppin, Andrew Strait, and Jenny Brennan. 2023. Going public: the role of public participation approaches in commercial AI labs. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1162–1173. Halfaker and Geiger (2020) Aaron Halfaker and R Stuart Geiger. 2020. ORES: Lowering Barriers with Participatory Machine Learning in Wikipedia. Proceedings of the ACM on Human-Computer Interaction 4, CSCW2 (Oct. 2020), 1–37. Hayes (2011) Gillian R Hayes. 2011. The Relationship of Action Research to Human-Computer Interaction. ACM Transactions on Computer-Human Interaction 18, 3 (Aug. 2011), 1–20. Hoffmann (2019) Anna Lauren Hoffmann. 2019. Where fairness fails: data, algorithms, and the limits of antidiscrimination discourse. Information, Communication & Society 22, 7 (June 2019), 900–915. Hu et al. (2019) Xianhong Hu, Bhanu Neupane, Lucia Flores Echaiz, Prateek Sibal, and Macarena Rivera Lam. 2019. Steering AI and Advanced ICTs for Knowledge Societies. United Nations Educational, Scientific and Cultural Organization (UNESCO), Paris, France. Hutchinson et al. (2020) Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Aaron Halfaker and R Stuart Geiger. 2020. ORES: Lowering Barriers with Participatory Machine Learning in Wikipedia. Proceedings of the ACM on Human-Computer Interaction 4, CSCW2 (Oct. 2020), 1–37. Hayes (2011) Gillian R Hayes. 2011. The Relationship of Action Research to Human-Computer Interaction. ACM Transactions on Computer-Human Interaction 18, 3 (Aug. 2011), 1–20. Hoffmann (2019) Anna Lauren Hoffmann. 2019. Where fairness fails: data, algorithms, and the limits of antidiscrimination discourse. Information, Communication & Society 22, 7 (June 2019), 900–915. Hu et al. (2019) Xianhong Hu, Bhanu Neupane, Lucia Flores Echaiz, Prateek Sibal, and Macarena Rivera Lam. 2019. Steering AI and Advanced ICTs for Knowledge Societies. United Nations Educational, Scientific and Cultural Organization (UNESCO), Paris, France. Hutchinson et al. (2020) Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Gillian R Hayes. 2011. The Relationship of Action Research to Human-Computer Interaction. ACM Transactions on Computer-Human Interaction 18, 3 (Aug. 2011), 1–20. Hoffmann (2019) Anna Lauren Hoffmann. 2019. Where fairness fails: data, algorithms, and the limits of antidiscrimination discourse. Information, Communication & Society 22, 7 (June 2019), 900–915. Hu et al. (2019) Xianhong Hu, Bhanu Neupane, Lucia Flores Echaiz, Prateek Sibal, and Macarena Rivera Lam. 2019. Steering AI and Advanced ICTs for Knowledge Societies. United Nations Educational, Scientific and Cultural Organization (UNESCO), Paris, France. Hutchinson et al. (2020) Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Anna Lauren Hoffmann. 2019. Where fairness fails: data, algorithms, and the limits of antidiscrimination discourse. Information, Communication & Society 22, 7 (June 2019), 900–915. Hu et al. (2019) Xianhong Hu, Bhanu Neupane, Lucia Flores Echaiz, Prateek Sibal, and Macarena Rivera Lam. 2019. Steering AI and Advanced ICTs for Knowledge Societies. United Nations Educational, Scientific and Cultural Organization (UNESCO), Paris, France. Hutchinson et al. (2020) Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Xianhong Hu, Bhanu Neupane, Lucia Flores Echaiz, Prateek Sibal, and Macarena Rivera Lam. 2019. Steering AI and Advanced ICTs for Knowledge Societies. United Nations Educational, Scientific and Cultural Organization (UNESCO), Paris, France. Hutchinson et al. (2020) Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  39. Judith Gregory. 2003. Scandinavian approaches to participatory design. International Journal of Engineering Education 19, 1 (2003), 62–74. Groves et al. (2023) Lara Groves, Aidan Peppin, Andrew Strait, and Jenny Brennan. 2023. Going public: the role of public participation approaches in commercial AI labs. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1162–1173. Halfaker and Geiger (2020) Aaron Halfaker and R Stuart Geiger. 2020. ORES: Lowering Barriers with Participatory Machine Learning in Wikipedia. Proceedings of the ACM on Human-Computer Interaction 4, CSCW2 (Oct. 2020), 1–37. Hayes (2011) Gillian R Hayes. 2011. The Relationship of Action Research to Human-Computer Interaction. ACM Transactions on Computer-Human Interaction 18, 3 (Aug. 2011), 1–20. Hoffmann (2019) Anna Lauren Hoffmann. 2019. Where fairness fails: data, algorithms, and the limits of antidiscrimination discourse. Information, Communication & Society 22, 7 (June 2019), 900–915. Hu et al. (2019) Xianhong Hu, Bhanu Neupane, Lucia Flores Echaiz, Prateek Sibal, and Macarena Rivera Lam. 2019. Steering AI and Advanced ICTs for Knowledge Societies. United Nations Educational, Scientific and Cultural Organization (UNESCO), Paris, France. Hutchinson et al. (2020) Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lara Groves, Aidan Peppin, Andrew Strait, and Jenny Brennan. 2023. Going public: the role of public participation approaches in commercial AI labs. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1162–1173. Halfaker and Geiger (2020) Aaron Halfaker and R Stuart Geiger. 2020. ORES: Lowering Barriers with Participatory Machine Learning in Wikipedia. Proceedings of the ACM on Human-Computer Interaction 4, CSCW2 (Oct. 2020), 1–37. Hayes (2011) Gillian R Hayes. 2011. The Relationship of Action Research to Human-Computer Interaction. ACM Transactions on Computer-Human Interaction 18, 3 (Aug. 2011), 1–20. Hoffmann (2019) Anna Lauren Hoffmann. 2019. Where fairness fails: data, algorithms, and the limits of antidiscrimination discourse. Information, Communication & Society 22, 7 (June 2019), 900–915. Hu et al. (2019) Xianhong Hu, Bhanu Neupane, Lucia Flores Echaiz, Prateek Sibal, and Macarena Rivera Lam. 2019. Steering AI and Advanced ICTs for Knowledge Societies. United Nations Educational, Scientific and Cultural Organization (UNESCO), Paris, France. Hutchinson et al. (2020) Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Aaron Halfaker and R Stuart Geiger. 2020. ORES: Lowering Barriers with Participatory Machine Learning in Wikipedia. Proceedings of the ACM on Human-Computer Interaction 4, CSCW2 (Oct. 2020), 1–37. Hayes (2011) Gillian R Hayes. 2011. The Relationship of Action Research to Human-Computer Interaction. ACM Transactions on Computer-Human Interaction 18, 3 (Aug. 2011), 1–20. Hoffmann (2019) Anna Lauren Hoffmann. 2019. Where fairness fails: data, algorithms, and the limits of antidiscrimination discourse. Information, Communication & Society 22, 7 (June 2019), 900–915. Hu et al. (2019) Xianhong Hu, Bhanu Neupane, Lucia Flores Echaiz, Prateek Sibal, and Macarena Rivera Lam. 2019. Steering AI and Advanced ICTs for Knowledge Societies. United Nations Educational, Scientific and Cultural Organization (UNESCO), Paris, France. Hutchinson et al. (2020) Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Gillian R Hayes. 2011. The Relationship of Action Research to Human-Computer Interaction. ACM Transactions on Computer-Human Interaction 18, 3 (Aug. 2011), 1–20. Hoffmann (2019) Anna Lauren Hoffmann. 2019. Where fairness fails: data, algorithms, and the limits of antidiscrimination discourse. Information, Communication & Society 22, 7 (June 2019), 900–915. Hu et al. (2019) Xianhong Hu, Bhanu Neupane, Lucia Flores Echaiz, Prateek Sibal, and Macarena Rivera Lam. 2019. Steering AI and Advanced ICTs for Knowledge Societies. United Nations Educational, Scientific and Cultural Organization (UNESCO), Paris, France. Hutchinson et al. (2020) Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Anna Lauren Hoffmann. 2019. Where fairness fails: data, algorithms, and the limits of antidiscrimination discourse. Information, Communication & Society 22, 7 (June 2019), 900–915. Hu et al. (2019) Xianhong Hu, Bhanu Neupane, Lucia Flores Echaiz, Prateek Sibal, and Macarena Rivera Lam. 2019. Steering AI and Advanced ICTs for Knowledge Societies. United Nations Educational, Scientific and Cultural Organization (UNESCO), Paris, France. Hutchinson et al. (2020) Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Xianhong Hu, Bhanu Neupane, Lucia Flores Echaiz, Prateek Sibal, and Macarena Rivera Lam. 2019. Steering AI and Advanced ICTs for Knowledge Societies. United Nations Educational, Scientific and Cultural Organization (UNESCO), Paris, France. Hutchinson et al. (2020) Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  40. Going public: the role of public participation approaches in commercial AI labs. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1162–1173. Halfaker and Geiger (2020) Aaron Halfaker and R Stuart Geiger. 2020. ORES: Lowering Barriers with Participatory Machine Learning in Wikipedia. Proceedings of the ACM on Human-Computer Interaction 4, CSCW2 (Oct. 2020), 1–37. Hayes (2011) Gillian R Hayes. 2011. The Relationship of Action Research to Human-Computer Interaction. ACM Transactions on Computer-Human Interaction 18, 3 (Aug. 2011), 1–20. Hoffmann (2019) Anna Lauren Hoffmann. 2019. Where fairness fails: data, algorithms, and the limits of antidiscrimination discourse. Information, Communication & Society 22, 7 (June 2019), 900–915. Hu et al. (2019) Xianhong Hu, Bhanu Neupane, Lucia Flores Echaiz, Prateek Sibal, and Macarena Rivera Lam. 2019. Steering AI and Advanced ICTs for Knowledge Societies. United Nations Educational, Scientific and Cultural Organization (UNESCO), Paris, France. Hutchinson et al. (2020) Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Aaron Halfaker and R Stuart Geiger. 2020. ORES: Lowering Barriers with Participatory Machine Learning in Wikipedia. Proceedings of the ACM on Human-Computer Interaction 4, CSCW2 (Oct. 2020), 1–37. Hayes (2011) Gillian R Hayes. 2011. The Relationship of Action Research to Human-Computer Interaction. ACM Transactions on Computer-Human Interaction 18, 3 (Aug. 2011), 1–20. Hoffmann (2019) Anna Lauren Hoffmann. 2019. Where fairness fails: data, algorithms, and the limits of antidiscrimination discourse. Information, Communication & Society 22, 7 (June 2019), 900–915. Hu et al. (2019) Xianhong Hu, Bhanu Neupane, Lucia Flores Echaiz, Prateek Sibal, and Macarena Rivera Lam. 2019. Steering AI and Advanced ICTs for Knowledge Societies. United Nations Educational, Scientific and Cultural Organization (UNESCO), Paris, France. Hutchinson et al. (2020) Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Gillian R Hayes. 2011. The Relationship of Action Research to Human-Computer Interaction. ACM Transactions on Computer-Human Interaction 18, 3 (Aug. 2011), 1–20. Hoffmann (2019) Anna Lauren Hoffmann. 2019. Where fairness fails: data, algorithms, and the limits of antidiscrimination discourse. Information, Communication & Society 22, 7 (June 2019), 900–915. Hu et al. (2019) Xianhong Hu, Bhanu Neupane, Lucia Flores Echaiz, Prateek Sibal, and Macarena Rivera Lam. 2019. Steering AI and Advanced ICTs for Knowledge Societies. United Nations Educational, Scientific and Cultural Organization (UNESCO), Paris, France. Hutchinson et al. (2020) Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Anna Lauren Hoffmann. 2019. Where fairness fails: data, algorithms, and the limits of antidiscrimination discourse. Information, Communication & Society 22, 7 (June 2019), 900–915. Hu et al. (2019) Xianhong Hu, Bhanu Neupane, Lucia Flores Echaiz, Prateek Sibal, and Macarena Rivera Lam. 2019. Steering AI and Advanced ICTs for Knowledge Societies. United Nations Educational, Scientific and Cultural Organization (UNESCO), Paris, France. Hutchinson et al. (2020) Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Xianhong Hu, Bhanu Neupane, Lucia Flores Echaiz, Prateek Sibal, and Macarena Rivera Lam. 2019. Steering AI and Advanced ICTs for Knowledge Societies. United Nations Educational, Scientific and Cultural Organization (UNESCO), Paris, France. Hutchinson et al. (2020) Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  41. Aaron Halfaker and R Stuart Geiger. 2020. ORES: Lowering Barriers with Participatory Machine Learning in Wikipedia. Proceedings of the ACM on Human-Computer Interaction 4, CSCW2 (Oct. 2020), 1–37. Hayes (2011) Gillian R Hayes. 2011. The Relationship of Action Research to Human-Computer Interaction. ACM Transactions on Computer-Human Interaction 18, 3 (Aug. 2011), 1–20. Hoffmann (2019) Anna Lauren Hoffmann. 2019. Where fairness fails: data, algorithms, and the limits of antidiscrimination discourse. Information, Communication & Society 22, 7 (June 2019), 900–915. Hu et al. (2019) Xianhong Hu, Bhanu Neupane, Lucia Flores Echaiz, Prateek Sibal, and Macarena Rivera Lam. 2019. Steering AI and Advanced ICTs for Knowledge Societies. United Nations Educational, Scientific and Cultural Organization (UNESCO), Paris, France. Hutchinson et al. (2020) Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Gillian R Hayes. 2011. The Relationship of Action Research to Human-Computer Interaction. ACM Transactions on Computer-Human Interaction 18, 3 (Aug. 2011), 1–20. Hoffmann (2019) Anna Lauren Hoffmann. 2019. Where fairness fails: data, algorithms, and the limits of antidiscrimination discourse. Information, Communication & Society 22, 7 (June 2019), 900–915. Hu et al. (2019) Xianhong Hu, Bhanu Neupane, Lucia Flores Echaiz, Prateek Sibal, and Macarena Rivera Lam. 2019. Steering AI and Advanced ICTs for Knowledge Societies. United Nations Educational, Scientific and Cultural Organization (UNESCO), Paris, France. Hutchinson et al. (2020) Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Anna Lauren Hoffmann. 2019. Where fairness fails: data, algorithms, and the limits of antidiscrimination discourse. Information, Communication & Society 22, 7 (June 2019), 900–915. Hu et al. (2019) Xianhong Hu, Bhanu Neupane, Lucia Flores Echaiz, Prateek Sibal, and Macarena Rivera Lam. 2019. Steering AI and Advanced ICTs for Knowledge Societies. United Nations Educational, Scientific and Cultural Organization (UNESCO), Paris, France. Hutchinson et al. (2020) Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Xianhong Hu, Bhanu Neupane, Lucia Flores Echaiz, Prateek Sibal, and Macarena Rivera Lam. 2019. Steering AI and Advanced ICTs for Knowledge Societies. United Nations Educational, Scientific and Cultural Organization (UNESCO), Paris, France. Hutchinson et al. (2020) Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  42. Gillian R Hayes. 2011. The Relationship of Action Research to Human-Computer Interaction. ACM Transactions on Computer-Human Interaction 18, 3 (Aug. 2011), 1–20. Hoffmann (2019) Anna Lauren Hoffmann. 2019. Where fairness fails: data, algorithms, and the limits of antidiscrimination discourse. Information, Communication & Society 22, 7 (June 2019), 900–915. Hu et al. (2019) Xianhong Hu, Bhanu Neupane, Lucia Flores Echaiz, Prateek Sibal, and Macarena Rivera Lam. 2019. Steering AI and Advanced ICTs for Knowledge Societies. United Nations Educational, Scientific and Cultural Organization (UNESCO), Paris, France. Hutchinson et al. (2020) Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Anna Lauren Hoffmann. 2019. Where fairness fails: data, algorithms, and the limits of antidiscrimination discourse. Information, Communication & Society 22, 7 (June 2019), 900–915. Hu et al. (2019) Xianhong Hu, Bhanu Neupane, Lucia Flores Echaiz, Prateek Sibal, and Macarena Rivera Lam. 2019. Steering AI and Advanced ICTs for Knowledge Societies. United Nations Educational, Scientific and Cultural Organization (UNESCO), Paris, France. Hutchinson et al. (2020) Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Xianhong Hu, Bhanu Neupane, Lucia Flores Echaiz, Prateek Sibal, and Macarena Rivera Lam. 2019. Steering AI and Advanced ICTs for Knowledge Societies. United Nations Educational, Scientific and Cultural Organization (UNESCO), Paris, France. Hutchinson et al. (2020) Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  43. Anna Lauren Hoffmann. 2019. Where fairness fails: data, algorithms, and the limits of antidiscrimination discourse. Information, Communication & Society 22, 7 (June 2019), 900–915. Hu et al. (2019) Xianhong Hu, Bhanu Neupane, Lucia Flores Echaiz, Prateek Sibal, and Macarena Rivera Lam. 2019. Steering AI and Advanced ICTs for Knowledge Societies. United Nations Educational, Scientific and Cultural Organization (UNESCO), Paris, France. Hutchinson et al. (2020) Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Xianhong Hu, Bhanu Neupane, Lucia Flores Echaiz, Prateek Sibal, and Macarena Rivera Lam. 2019. Steering AI and Advanced ICTs for Knowledge Societies. United Nations Educational, Scientific and Cultural Organization (UNESCO), Paris, France. Hutchinson et al. (2020) Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  44. Steering AI and Advanced ICTs for Knowledge Societies. United Nations Educational, Scientific and Cultural Organization (UNESCO), Paris, France. Hutchinson et al. (2020) Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl. 2020. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  45. Social Biases in NLP Models as Barriers for Persons with Disabilities. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 5491–5501. Katell et al. (2020) Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael Katell, Meg Young, Dharma Dailey, Bernease Herman, Vivian Guetler, Aaron Tam, Corinne Bintz, Daniella Raz, and P M Krafft. 2020. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  46. Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* '20). Association for Computing Machinery, New York, NY, USA, 45–55. Kensing and Blomberg (1998) Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  47. Finn Kensing and Jeanette Blomberg. 1998. Participatory Design: Issues and Concerns. Computer Supported Cooperative Work 7, 3 (Sept. 1998), 167–185. Keyes (2018) Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  48. Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–22. Kulynych et al. (2020) Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Bogdan Kulynych, David Madras, Smitha Milli, Inioluwa Deborah Raji, Zhou, and Richard Zemel. 2020. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  49. Participatory Approaches to Machine Learning. https://participatoryml.github.io/. Accessed: 2022-10-12. Lee et al. (2019) Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, and Ariel D Procaccia. 2019. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  50. WeBuildAI: Participatory Framework for Algorithmic Governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (Nov. 2019), 1–35. Mayer-Schönberger and Cukier (2013) Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  51. Viktor Mayer-Schönberger and Kenneth Cukier. 2013. Big Data: A Revolution that Will Transform how We Live, Work, and Think. Houghton Mifflin Harcourt, Boston, MA, USA. Mohamed et al. (2020) Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shakir Mohamed, Marie-Therese Png, and William Isaac. 2020. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  52. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 4 (Dec. 2020), 659–684. Muller and Druin (2012) Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  53. Michael J Muller and Allison Druin. 2012. Participatory Design: The Third Space in Human–Computer Interaction. In The Human–Computer Interaction Handbook. CRC Press, Boca Raton, FL, USA, 1125–1153. Muller and Kuhn (1993) Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  54. Michael J Muller and Sarah Kuhn. 1993. Participatory Design. Commun. ACM 36, 6 (June 1993), 24–28. Nader (1972) Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  55. Laura Nader. 1972. Up the Anthropologist: Perspectives Gained From Studying Up. In Reinventing Anthropology, Dell Hymes (Ed.). Pantheon Books, Random House, New York. Nekoto et al. (2020) Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, Timi Fasubaa, Taiwo Fagbohungbe, Solomon Oluwole Akinola, Shamsuddeen Muhammad, Salomon Kabongo Kabenamualu, Salomey Osei, Freshia Sackey, Rubungo Andre Niyongabo, Ricky Macharm, Perez Ogayo, Orevaoghene Ahia, Musie Meressa Berhe, Mofetoluwa Adeyemi, Masabata Mokgesi-Selinga, Lawrence Okegbemi, Laura Martinus, Kolawole Tajudeen, Kevin Degila, Kelechi Ogueji, Kathleen Siminyu, Julia Kreutzer, Jason Webster, Jamiil Toure Ali, Jade Abbott, Iroro Orife, Ignatius Ezeani, Idris Abdulkadir Dangana, Herman Kamper, Hady Elsahar, Goodness Duru, Ghollah Kioko, Murhabazi Espoir, Elan van Biljon, Daniel Whitenack, Christopher Onyefuluchi, Chris Chinenye Emezue, Bonaventure F P Dossou, Blessing Sibanda, Blessing Bassey, Ayodele Olabiyi, Arshath Ramkilowan, Alp Öktem, Adewale Akinfaderin, and Abdallah Bashir. 2020. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  56. Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 2144–2160. https://doi.org/10.18653/v1/2020.findings-emnlp.195 Noble (2018) Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  57. Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, NY, USA. Palinkas et al. (2015) Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lawrence A Palinkas, Sarah M Horwitz, Carla A Green, Jennifer P Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  58. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Adm. Policy Ment. Health 42, 5 (Sept. 2015), 533–544. Patton et al. (2020) Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Desmond U Patton, Fei-Tzin Lee, William R Frey, Kathleen McKeown, Kyle A McGregor, and Emanuel Moss. 2020. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  59. Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 2020 (Feb. 2020), 337–342. Prabhakaran and Martin (2020) Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  60. Vinodkumar Prabhakaran and Donald Martin, Jr. 2020. Participatory Machine Learning Using Community-Based System Dynamics. Health and Human Rights Journal 22, 2 (Dec. 2020), 71–74. Pushkarna et al. (2022) Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mahima Pushkarna, Andrew Zaldivar, and Oddur Kjartansson. 2022. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  61. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT '22). Association for Computing Machinery, New York, NY, USA, 1776–1826. https://doi.org/10.1145/3531146.3533231 Queerinai et al. (2023) Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Organizers Of Queerinai, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx Mclean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, and Luke Stark. 2023. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  62. Queer In AI: A Case Study in Community-Led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 1882–1895. https://doi.org/10.1145/3593013.3594134 Robertson and Salehi (2020) Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  63. Samantha Robertson and Niloufar Salehi. 2020. What If I Don't Like Any Of The Choices? The Limits of Preference Elicitation for Participatory Algorithm Design. arXiv:2007.06718 [cs.CY] Sambasivan and Veeraraghavan (2022) Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  64. Nithya Sambasivan and Rajesh Veeraraghavan. 2022. The Deskilling of Domain Expertise in AI Development. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22, Article 587). Association for Computing Machinery, New York, NY, USA, 1–14. Savoldi et al. (2021) Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  65. Gender Bias in Machine Translation. Transactions of the Association for Computational Linguistics (TACL) 9 (Aug. 2021), 845–874. Schuler and Namioka (1993) Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  66. Douglas Schuler and Aki Namioka. 1993. Participatory Design: Principles and Practices. CRC Press, Boca Raton, FL, USA. Selbst et al. (2019) Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Andrew D Selbst, Danah Boyd, Sorelle A Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  67. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* '19). Association for Computing Machinery, New York, NY, USA, 59–68. Singh et al. (2022) Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Ranjit Singh, Rigoberto Lara Guzmán, and Patrick Davison. 2022. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  68. Parables of AI in/from the Majority World. (Dec. 2022). https://doi.org/10.2139/ssrn.4258527 Sloane et al. (2022) Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Mona Sloane, Emanuel Moss, Olaitan Awomolo, and Laura Forlano. 2022. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  69. Participation Is not a Design Fix for Machine Learning. In Equity and Access in Algorithms, Mechanisms, and Optimization (Arlington, VA, USA) (EAAMO '22, Article 1). Association for Computing Machinery, New York, NY, USA, 1–6. Sundblad (2011) Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  70. Yngve Sundblad. 2011. UTOPIA: Participatory Design from Scandinavia to the World. In History of Nordic Computing 3, John Impagliazzo, Per Lundin, and Benkt Wangler (Eds.). Springer, Berlin, Germany; London, UK, 176–186. Suresh et al. (2022) Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Harini Suresh, Rajiv Movva, Amelia Lee Dogan, Rahul Bhargava, Isadora Cruxen, Angeles Martinez Cuba, Guilia Taurino, Wonyoung So, and Catherine D'Ignazio. 2022. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  71. Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. In 2022 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery, Seoul, Republic of Korea, 667–678. Theodorou et al. (2021) Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, and Katja Hofmann. 2021. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  72. Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (Virtual Event, USA) (ASSETS '21, Article 27). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3441852.3471225 Venkit et al. (2022) Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Pranav Narayanan Venkit, Mukund Srinath, and Shomir Wilson. 2022. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  73. A Study of Implicit Bias in Pretrained Language Models against People with Disabilities. In Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 1324–1332. Vines et al. (2013) John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. John Vines, Rachel Clarke, Peter Wright, John McCarthy, and Patrick Olivier. 2013. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  74. Configuring participation: on how we involve people in design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 429–438. Warren (2001) Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  75. Carol A B Warren. 2001. Qualitative Interviewing. In Handbook of Interview Research. SAGE Publications Ltd, Thousand Oaks, California, USA, 83–102. White House Office of Science and Technology Policy (2021) White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  76. White House Office of Science and Technology Policy. 2021. Artificial Intelligence and Democratic Values. Zhang et al. (2023) Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Angie Zhang, Olympia Walker, Kaci Nguyen, Jiajun Dai, Anqing Chen, and Min Kyung Lee. 2023. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  77. Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (April 2023), 1–32. Zhu et al. (2018) Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Haiyi Zhu, Bowen Yu, Aaron Halfaker, and Loren Terveen. 2018. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  78. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (Nov. 2018), 1–23. Ziewitz and Singh (2021) Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  79. Malte Ziewitz and Ranjit Singh. 2021. Critical Companionship: Some Sensibilities for Studying the Lived Experience of Data Subjects. Big Data & Society 8, 2 (July 2021), 20539517211061122. https://doi.org/10.1177/20539517211061122 Zong and Matias (2023) Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  80. Jonathan Zong and J Nathan Matias. 2023. Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design. ACM Journal on Responsible Computing (Oct. 2023). https://doi.org/10.1145/3630107 Zuboff (2019) Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  81. Shoshana Zuboff. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books, London, UK. Zytko et al. (2022) Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4. Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric P. S. Baumer, and Min Kyung Lee. 2022. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
  82. Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA '22, Article 154). Association for Computing Machinery, New York, NY, USA, 1–4.
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