Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
102 tokens/sec
GPT-4o
59 tokens/sec
Gemini 2.5 Pro Pro
43 tokens/sec
o3 Pro
6 tokens/sec
GPT-4.1 Pro
50 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

BLIP: Facilitating the Exploration of Undesirable Consequences of Digital Technologies (2405.06783v1)

Published 10 May 2024 in cs.HC, cs.AI, and cs.CY

Abstract: Digital technologies have positively transformed society, but they have also led to undesirable consequences not anticipated at the time of design or development. We posit that insights into past undesirable consequences can help researchers and practitioners gain awareness and anticipate potential adverse effects. To test this assumption, we introduce BLIP, a system that extracts real-world undesirable consequences of technology from online articles, summarizes and categorizes them, and presents them in an interactive, web-based interface. In two user studies with 15 researchers in various computer science disciplines, we found that BLIP substantially increased the number and diversity of undesirable consequences they could list in comparison to relying on prior knowledge or searching online. Moreover, BLIP helped them identify undesirable consequences relevant to their ongoing projects, made them aware of undesirable consequences they "had never considered," and inspired them to reflect on their own experiences with technology.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (118)
  1. IUI Program Chairs 2024. [n. d.]. Reflecting on Societal Implications of IUI Research. https://iui.acm.org/2024/societal_impact.html, last accessed: February 27, 2024.
  2. Grace Abuhamad and Claudel Rheault. 2020. Like a Researcher Stating Broader Impact For the Very First Time. arXiv:2011.13032 [cs.CY]
  3. Privacy and human behavior in the age of information. Science 347, 6221 (2015), 509–514.
  4. Guidelines for Human-AI Interaction. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk) (CHI ’19). Association for Computing Machinery, New York, NY, USA, 1–13. https://doi.org/10.1145/3290605.3300233
  5. Categorizing the unintended sociotechnical consequences of computerized provider order entry. International journal of medical informatics 76 (2007), S21–S27.
  6. AI Ethics Statements: Analysis and Lessons Learnt from NeurIPS Broader Impact Statements. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea) (FAccT ’22). Association for Computing Machinery, New York, NY, USA, 2047–2056. https://doi.org/10.1145/3531146.3533780
  7. Paper Plain: Making Medical Research Papers Approachable to Healthcare Consumers with Natural Language Processing. ACM Transactions on Computer-Human Interaction 30, 5, Article 74 (sep 2023), 38 pages. https://doi.org/10.1145/3589955
  8. AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias. IBM J. Res. Dev. 63 (2019), 4:1–4:15.
  9. Emily M. Bender and Batya Friedman. 2018. Data Statements for Natural Language Processing: Toward Mitigating System Bias and Enabling Better Science. Transactions of the Association for Computational Linguistics 6 (2018), 587–604. https://doi.org/10.1162/tacl_a_00041
  10. Ethics and society review: Ethics reflection as a precondition to research funding. Proceedings of the National Academy of Sciences 118, 52 (2021), e2117261118. https://doi.org/10.1073/pnas.2117261118 arXiv:https://www.pnas.org/doi/pdf/10.1073/pnas.2117261118
  11. Introducing the NeurIPS 2021 Paper Checklist. https://neuripsconf.medium.com/introducing-the-neurips-2021-paper-checklist-3220d6df500b
  12. The’invisible’materiality of information technology. Commun. ACM 63, 6 (2020), 57–64.
  13. Language Models are Few-Shot Learners. In Advances in Neural Information Processing Systems, H. Larochelle, M. Ranzato, R. Hadsell, M.F. Balcan, and H. Lin (Eds.), Vol. 33. Curran Associates, Inc., 1877–1901. https://proceedings.neurips.cc/paper_files/paper/2020/file/1457c0d6bfcb4967418bfb8ac142f64a-Paper.pdf
  14. Amy Bruckman. 2020. ’Have You Thought About…’: Talking about Ethical Implications of Research. Commun. ACM 63, 9 (aug 2020), 38–40. https://doi.org/10.1145/3377405
  15. Sparks of Artificial General Intelligence: Early experiments with GPT-4. arXiv:2303.12712 [cs.CL]
  16. AHA!: Facilitating AI Impact Assessment by Generating Examples of Harms. arXiv:2306.03280 [cs.HC]
  17. 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, 77–91. https://proceedings.mlr.press/v81/buolamwini18a.html
  18. Unintended Consequences of Machine Learning in Medicine. JAMA 318, 6 (08 2017), 517–518. https://doi.org/10.1001/jama.2017.7797
  19. FAIRVIS: Visual Analytics for Discovering Intersectional Bias in Machine Learning. In 2019 IEEE Conference on Visual Analytics Science and Technology (VAST). IEEE Computer Society, Los Alamitos, CA, USA, 46–56. https://doi.org/10.1109/VAST47406.2019.8986948
  20. Comms Chairs. 2021. NeurIPS 2021 Ethics Guidelines. https://blog.neurips.cc/2021/08/23/neurips-2021-ethics-guidelines/
  21. A fuzzy multiple criteria comparison of technology forecasting methods for predicting the new materials development. Technological Forecasting and Social Change 75 (2008), 131–141.
  22. Surveying the Landscape of Ethics-Focused Design Methods. arXiv:2102.08909 [cs.HC]
  23. Decontextualization: Making sentences stand-alone. Transactions of the Association for Computational Linguistics 9 (2021), 447–461.
  24. Julian Chokkattu. 2019. Google assistant can now translate speech through your phone. https://www.wired.com/story/google-assistant-can-now-translate-on-your-phone/
  25. Social media and depression symptoms: a meta-analysis. Research on child and adolescent psychopathology 49, 2 (2021), 241–253.
  26. Fine-Grained Analysis of Propaganda in News Article. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), Kentaro Inui, Jing Jiang, Vincent Ng, and Xiaojun Wan (Eds.). Association for Computational Linguistics, Hong Kong, China, 5636–5646. https://doi.org/10.18653/v1/D19-1565
  27. Frank De Zwart. 2015. Unintended but not unanticipated consequences. Theory and Society 44, 3 (2015), 283–297.
  28. The spreading of misinformation online. Proceedings of the National Academy of Sciences 113, 3 (2016), 554–559.
  29. The Idea Machine: LLM-Based Expansion, Rewriting, Combination, and Suggestion of Ideas. In Proceedings of the 14th Conference on Creativity and Cognition (Venice, Italy) (C&C ’22). Association for Computing Machinery, New York, NY, USA, 623–627. https://doi.org/10.1145/3527927.3535197
  30. Does the Sharing Economy do any Good?. In Proceedings of the 19th ACM Conference on Computer Supported Cooperative Work and Social Computing Companion (San Francisco, California, USA) (CSCW ’16 Companion). Association for Computing Machinery, New York, NY, USA, 197–200. https://doi.org/10.1145/2818052.2893362
  31. “That’s Important, but…”: How Computer Science Researchers Anticipate Unintended Consequences of Their Research Innovations. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (Hamburg, Germany) (CHI ’23). Association for Computing Machinery, New York, NY, USA, Article 602, 16 pages. https://doi.org/10.1145/3544548.3581347
  32. All The Cool Kids, How Do They Fit In?: Popularity and Demographic Biases in Recommender Evaluation and Effectiveness. 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, 172–186. https://proceedings.mlr.press/v81/ekstrand18b.html
  33. J. Morley English and Gerard L. Kernan. 1976. THE PREDICTION OF AIR TRAVEL AND AIRCRAFT TECHNOLOGY TO THE YEAR 2000 USING THE DELPHI METHOD. Transportation Research 10 (1976), 1–8.
  34. Reinventing the Wheel: The Future Ripples Method for Activating Anticipatory Capacities in Innovation Teams. In Proceedings of the 2022 ACM Designing Interactive Systems Conference (¡conf-loc¿, ¡city¿Virtual Event¡/city¿, ¡country¿Australia¡/country¿, ¡/conf-loc¿) (DIS ’22). Association for Computing Machinery, New York, NY, USA, 387–399. https://doi.org/10.1145/3532106.3534570
  35. ACL establishes its Ethics Committee. https://www.aclweb.org/portal/content/acl-establishes-its-ethics-committee
  36. Batya Friedman and David Hendry. 2012. The Envisioning Cards: A Toolkit for Catalyzing Humanistic and Technical Imaginations. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Austin, Texas, USA) (CHI ’12). Association for Computing Machinery, New York, NY, USA, 1145–1148. https://doi.org/10.1145/2207676.2208562
  37. Value Sensitive Design and Information Systems. Springer Netherlands, Dordrecht, 55–95. https://doi.org/10.1007/978-94-007-7844-3_4
  38. Datasheets for datasets. Commun. ACM 64, 12 (2021), 86–92.
  39. Jerry Glenn. 1972. Futurizing Teaching vs. Futures Courses. Social Science Record (1972). https://api.semanticscholar.org/CorpusID:141272607
  40. Colin M. Gray and Shruthi Sai Chivukula. 2019. Ethical Mediation in UX Practice. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk) (CHI ’19). Association for Computing Machinery, New York, NY, USA, 1–11. https://doi.org/10.1145/3290605.3300408
  41. Artefact Group. 2017. The Tarot Cards of Tech. last accessed February 27, 2024.
  42. Karen Hao. 2021. Ai voice actors sound more human than ever-and they’re ready to hire. https://www.technologyreview.com/2021/07/09/1028140/ai-voice-actors-sound-human/
  43. Unintended consequences of information technologies in health care—an interactive sociotechnical analysis. Journal of the American medical informatics Association 14, 5 (2007), 542–549.
  44. It’s Time to Do Something: Mitigating the Negative Impacts of Computing Through a Change to the Peer Review Process. arXiv:2112.09544 [cs.CY]
  45. The Curious Case of Neural Text Degeneration. In 8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020. OpenReview.net. https://openreview.net/forum?id=rygGQyrFvH
  46. Jason Huggins. 2018. Selenium with Python. Retrieved 2021-04-06 from https://selenium-python.readthedocs.io/
  47. Anna Iovine. 2021. Amazon Alexa told a 10-year-old to plug a charger into electrical outlet. https://mashable.com/article/alexa-wall-electrical-outlet-challenge-mistake
  48. Billion-scale similarity search with GPUs. IEEE Transactions on Big Data 7, 3 (2019), 535–547.
  49. Defects4J: a database of existing faults to enable controlled testing studies for Java programs. In Proceedings of the 2014 International Symposium on Software Testing and Analysis (San Jose, CA, USA) (ISSTA 2014). Association for Computing Machinery, New York, NY, USA, 437–440. https://doi.org/10.1145/2610384.2628055
  50. Threddy: An Interactive System for Personalized Thread-based Exploration and Organization of Scientific Literature. In Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology (Bend, OR, USA) (UIST ’22). Association for Computing Machinery, New York, NY, USA, Article 94, 15 pages. https://doi.org/10.1145/3526113.3545660
  51. Paragon: An Online Gallery for Enhancing Design Feedback with Visual Examples. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (Montreal QC, Canada) (CHI ’18). Association for Computing Machinery, New York, NY, USA, 1–13. https://doi.org/10.1145/3173574.3174180
  52. Picture perfect: The direct effect of manipulated Instagram photos on body image in adolescent girls. Media Psychology 21, 1 (2018), 93–110.
  53. It is time for more critical CS education. Commun. ACM 63, 11 (2020), 31–33.
  54. Fuse: In-Situ Sensemaking Support in the Browser. In Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology (Bend, OR, USA) (UIST ’22). Association for Computing Machinery, New York, NY, USA, Article 34, 15 pages. https://doi.org/10.1145/3526113.3545693
  55. Bilal Kılıç and Semih Soran. 2019. How Can an Ab-Initio Pilot Avert a Future Disaster: A Pedagogical Approach to Reduce The Likelihood of Future Failure. Journal of Aviation 3, 1 (2019), 1 – 14. https://doi.org/10.30518/jav.508336
  56. Implications for Adoption. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (Denver, Colorado, USA) (CHI ’17). Association for Computing Machinery, New York, NY, USA, 265–277. https://doi.org/10.1145/3025453.3025742
  57. Quantifying drug-induced dyskinesias in the arms using digitised spiral-drawing tasks. Journal of Neuroscience Methods 144, 1 (May 2005), 47–52.
  58. Ingrid Lunden. 2016. Improbable teams with Google, opens Spatialos Alpha for virtual world development. https://techcrunch.com/2016/12/13/improbable-teams-with-google-opens-spatialos-alpha-for-virtual-world-development/
  59. Making the News: Digital Creativity Support for Journalists (CHI ’18). Association for Computing Machinery, New York, NY, USA, 1–11. https://doi.org/10.1145/3173574.3174049
  60. Joseph P Martino. 2003. A review of selected recent advances in technological forecasting. Technological forecasting and social change 70, 8 (2003), 719–733.
  61. Jeanna Matthews. 2022. Embracing Critical Voices. Commun. ACM 65, 7 (Jun 2022), 7. https://doi.org/10.1145/3535268
  62. On Faithfulness and Factuality in Abstractive Summarization. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Online, 1906–1919. https://doi.org/10.18653/v1/2020.acl-main.173
  63. Reliability and inter-rater reliability in qualitative research: Norms and guidelines for CSCW and HCI practice. Proceedings of the ACM on human-computer interaction 3, CSCW (2019), 1–23.
  64. Sean McGregor. 2021. Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database. Proceedings of the AAAI Conference on Artificial Intelligence 35, 17 (May 2021), 15458–15463. https://doi.org/10.1609/aaai.v35i17.17817
  65. Robert K Merton. 1936. The Unanticipated Consequences of Purposive Social Action. American sociological review 1, 6 (1936), 894–904.
  66. Rachel Metz. 2020. The nauseating disappointment of Oculus rift. https://www.technologyreview.com/2016/05/05/245975/the-nauseating-disappointment-of-oculus-rift/
  67. Model Cards for Model Reporting. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* ’19). Association for Computing Machinery, New York, NY, USA, 220–229. https://doi.org/10.1145/3287560.3287596
  68. Saif Mohammad. 2022. Ethics Sheets for AI Tasks. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, Dublin, Ireland, 8368–8379. https://doi.org/10.18653/v1/2022.acl-long.573
  69. Technology at the Table: Attitudes About Mobile Phone Use at Mealtimes. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI) (Santa Clara, California, USA) (CHI ’16). ACM, New York, NY, USA, 1881–1892. https://doi.org/10.1145/2858036.2858357
  70. Anticipatory Ethics and the Role of Uncertainty. arXiv:2011.13170 [cs.CY]
  71. Unpacking the Expressed Consequences of AI Research in Broader Impact Statements. In Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society (Virtual Event, USA) (AIES ’21). Association for Computing Machinery, New York, NY, USA, 795–806. https://doi.org/10.1145/3461702.3462608
  72. Poster: A First Look at the Privacy Risks of Voice Assistant Apps. In Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security (London, United Kingdom) (CCS ’19). Association for Computing Machinery, New York, NY, USA, 2633–2635. https://doi.org/10.1145/3319535.3363274
  73. Peter G Neumann. 2008. The Risks Digest. The Risks Digest (2008). http://catless.ncl.ac.uk/Risks/
  74. Interactive Guidance Techniques for Improving Creative Feedback. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (Montreal QC, Canada) (CHI ’18). Association for Computing Machinery, New York, NY, USA, 1–11. https://doi.org/10.1145/3173574.3173629
  75. Shöwn: Adaptive Conceptual Guidance Aids Example Use in Creative Tasks. In Proceedings of the 2021 ACM Designing Interactive Systems Conference (Virtual Event, USA) (DIS ’21). Association for Computing Machinery, New York, NY, USA, 1834–1845. https://doi.org/10.1145/3461778.3462072
  76. John Nworie. 2011. Using the Delphi Technique in Educational Technology Research. TechTrends 55 (2011), 24–30.
  77. OpenAI. [n. d.]. Models. https://platform.openai.com/docs/models/gpt-3
  78. Lucas Ou-Yang. 2013. Newspaper3k: Article scraping & curation. Retrieved 2022-04-06 from https://newspaper.readthedocs.io/en/latest/
  79. Auditing Cross-Cultural Consistency of Human-Annotated Labels for Recommendation Systems. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (, Chicago, IL, USA,) (FAccT ’23). Association for Computing Machinery, New York, NY, USA, 1531–1552. https://doi.org/10.1145/3593013.3594098
  80. The Case for Anticipating Undesirable Consequences of Computing Innovations Early, Often, and Across Computer Science. arXiv:2309.04456 [cs.CY]
  81. Rock Yuren Pang and Katharina Reinecke. 2023. Anticipating Unintended Consequences of Technology Using Insights from Creativity Support Tools. arXiv:2304.05687 [cs.HC]
  82. Social Simulacra: Creating Populated Prototypes for Social Computing Systems. In Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology (Bend, OR, USA) (UIST ’22). Association for Computing Machinery, New York, NY, USA, Article 74, 18 pages. https://doi.org/10.1145/3526113.3545616
  83. Nassim Parvin and Anne Pollock. 2020. Unintended by Design: On the Political Uses of “Unintended Consequences”. Engaging Science, Technology, and Society 6 (2020), 320–327.
  84. AngleKindling: Supporting Journalistic Angle Ideation with Large Language Models. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (Hamburg, Germany) (CHI ’23). Association for Computing Machinery, New York, NY, USA, Article 225, 16 pages. https://doi.org/10.1145/3544548.3580907
  85. Modeling Naive Psychology of Characters in Simple Commonsense Stories. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, Melbourne, Australia, 2289–2299. https://doi.org/10.18653/v1/P18-1213
  86. Katharina Reinecke and Abraham Bernstein. 2011. Improving performance, perceived usability, and aesthetics with culturally adaptive user interfaces. ACM Trans. Comput.-Hum. Interact. 18, 2, Article 8 (jul 2011), 29 pages. https://doi.org/10.1145/1970378.1970382
  87. The unintended consequences of digital technology: Exploring the relationship between sexting and cybervictimization. Journal of Crime and Justice 36, 1 (2013), 1–17.
  88. Leonard Richardson. 2020. Beautiful Soup Documentation. Retrieved 2021-04-06 from https://www.crummy.com/software/BeautifulSoup/bs4/doc/
  89. Anna Rogers. 2021. Changing the World by Changing the Data. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). Association for Computational Linguistics, Online, 2182–2194. https://doi.org/10.18653/v1/2021.acl-long.170
  90. Basic objects in natural categories. Cognitive Psychology 8 (1976), 382–439.
  91. Tate Ryan-Mosley. 2021. How digital beauty filters perpetuate colorism. https://www.technologyreview.com/2021/08/15/1031804/digital-beauty-filters-photoshop-photo-editing-colorism-racism
  92. NLPositionality: Characterizing Design Biases of Datasets and Models. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Anna Rogers, Jordan Boyd-Graber, and Naoaki Okazaki (Eds.). Association for Computational Linguistics, Toronto, Canada, 9080–9102. https://doi.org/10.18653/v1/2023.acl-long.505
  93. Let’s talk about race: Identity, chatbots, and AI. In Proceedings of the 2018 chi conference on human factors in computing systems. 1–14.
  94. Value Cards: An Educational Toolkit for Teaching Social Impacts of Machine Learning through Deliberation. In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (Virtual Event, Canada) (FAccT ’21). Association for Computing Machinery, New York, NY, USA, 850–861. https://doi.org/10.1145/3442188.3445971
  95. Taeyoung Shin. 1998. Using Delphi for a Long-Range Technology Forecasting, and Assessing Directions of Future R&D Activities The Korean Exercise. Technological Forecasting and Social Change 58 (1998), 125–154.
  96. IdeaHound: Improving Large-scale Collaborative Ideation with Crowd-Powered Real-time Semantic Modeling. In Proceedings of the 29th Annual Symposium on User Interface Software and Technology (Tokyo, Japan) (UIST ’16). Association for Computing Machinery, New York, NY, USA, 609–624. https://doi.org/10.1145/2984511.2984578
  97. Providing Timely Examples Improves the Quantity and Quality of Generated Ideas. In Proceedings of the 2015 ACM SIGCHI Conference on Creativity and Cognition (Glasgow, United Kingdom) (C&C ’15). ACM, New York, NY, USA, 83–92. https://doi.org/10.1145/2757226.2757230
  98. Ethics Education in Context: A Case Study of Novel Ethics Activities for the CS Classroom. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education (Baltimore, Maryland, USA) (SIGCSE ’18). Association for Computing Machinery, New York, NY, USA, 940–945. https://doi.org/10.1145/3159450.3159573
  99. Advancing ethics review practices in AI research. Nature Machine Intelligence 4, 12 (2022), 1061–1064.
  100. Kate Starbird. 2019. Disinformation’s spread: bots, trolls and all of us. Nature 571, 449 (2019).
  101. Amanda Stent. 2022. Guidelines for ethics reviewing. https://aclrollingreview.org/ethicsreviewertutorial
  102. Consequences, Schmonsequences! Considering the Future as Part of Publication and Peer Review in Computing Research. In Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems (Yokohama, Japan) (CHI EA ’21). Association for Computing Machinery, New York, NY, USA, Article 95, 4 pages. https://doi.org/10.1145/3411763.3441330
  103. Unintended and Undesirable consequences of Innovation. In Proceedings of the XX ISPIM Conference, K.R.E. Huizingh, S. Conn, M. Torkkeli, and I. Bitran (Eds.). The XX ISPIM Conference - The Future of Innovation ; Conference date: 21-06-2009 Through 24-06-2009.
  104. Google People + AI Research Team. 2021. People + AI guidebook. https://pair.withgoogle.com/guidebook/
  105. Llama 2: Open Foundation and Fine-Tuned Chat Models. arXiv:2307.09288 [cs.CL]
  106. Kentaro Toyama. 2015. Geek heresy: Rescuing social change from the cult of technology. PublicAffairs.
  107. Social media, political polarization, and political disinformation: A review of the scientific literature. Political polarization, and political disinformation: a review of the scientific literature (March 19, 2018) (2018).
  108. T.B. Ward. 1994. Structured Imagination: the Role of Category Structure in Exemplar Generation. Cognitive Psychology 27, 1 (1994), 1–40. https://doi.org/10.1006/cogp.1994.1010
  109. W Timothy Weaver. 1971. The Delphi forecasting method. The Phi Delta Kappan 52, 5 (1971), 267–271.
  110. Finetuned Language Models Are Zero-Shot Learners. arXiv:2109.01652 [cs.CL]
  111. The What-If Tool: Interactive Probing of Machine Learning Models. IEEE Transactions on Visualization & Computer Graphics 26, 01 (jan 2020), 56–65. https://doi.org/10.1109/TVCG.2019.2934619
  112. Why we should have seen that coming: comments on microsoft’s tay “experiment,” and wider implications. The ORBIT Journal 1, 2 (2017), 1–12.
  113. IdeateRelate: An Examples Gallery That Helps Creators Explore Ideas in Relation to Their Own. Proc. ACM Hum.-Comput. Interact. 5, CSCW2, Article 352 (oct 2021), 18 pages. https://doi.org/10.1145/3479496
  114. Roman V Yampolskiy. 2019. Predicting future AI failures from historic examples. foresight 21, 1 (2019), 138–152.
  115. Wikum: Bridging Discussion Forums and Wikis Using Recursive Summarization. In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (Portland, Oregon, USA) (CSCW ’17). Association for Computing Machinery, New York, NY, USA, 2082–2096. https://doi.org/10.1145/2998181.2998235
  116. Enhao Zhang and Nikola Banovic. 2021. Method for Exploring Generative Adversarial Networks (GANs) via Automatically Generated Image Galleries (CHI ’21). Association for Computing Machinery, New York, NY, USA, Article 76, 15 pages. https://doi.org/10.1145/3411764.3445714
  117. Benchmarking Large Language Models for News Summarization. Transactions of the Association for Computational Linguistics 12 (2023), 39–57. https://api.semanticscholar.org/CorpusID:256416014
  118. Value-Sensitive Algorithm Design: Method, Case Study, and Lessons. Proc. ACM Hum.-Comput. Interact. 2, CSCW, Article 194 (nov 2018), 23 pages. https://doi.org/10.1145/3274463
User Edit Pencil Streamline Icon: https://streamlinehq.com
Authors (4)
  1. Rock Yuren Pang (11 papers)
  2. Sebastin Santy (15 papers)
  3. René Just (19 papers)
  4. Katharina Reinecke (15 papers)
Citations (8)

Summary

We haven't generated a summary for this paper yet.

X Twitter Logo Streamline Icon: https://streamlinehq.com

Tweets