Papers
Topics
Authors
Recent
Search
2000 character limit reached

Understanding Driver Agency in RideSharing

Published 31 Dec 2023 in cs.HC and cs.CY | (2401.00356v1)

Abstract: Agency is an important human characteristic that users of automated complex technologies are usually denied. This affects the user's experience leading to decreased satisfaction and productivity. In this paper, we consider the ridesharing context and interviewed 7 drivers to understand the controls that would improve the agency they feel. The results show that they desire transparency, community and an effective ability to seek redress.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (44)
  1. ACM. 2018. ACM Code of Ethics and Professional Conduct. https://www.acm.org/code-of-ethics
  2. Deeppool: Distributed model-free algorithm for ride-sharing using deep reinforcement learning. IEEE Transactions on Intelligent Transportation Systems 20, 12 (2019), 4714–4727.
  3. Alan Borning and Michael Muller. 2012. Next steps for value sensitive design. In Proceedings of the SIGCHI conference on human factors in computing systems. 1125–1134.
  4. Jason Brownlee. 2019. A gentle introduction to Bayesian Belief Networks. https://machinelearningmastery.com/introduction-to-bayesian-belief-networks/
  5. “Why lose control?” A Study of Freelancers’ Experiences with Gig Economy Platforms. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. 1–14.
  6. Designing an on-line ride-sharing system. In Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems. 1–4.
  7. Mary L Cummings. 2006. Integrating ethics in design through the value-sensitive design approach. Science and engineering ethics 12, 4 (2006), 701–715.
  8. Self-determination theory in work organizations: The state of a science. Annual review of organizational psychology and organizational behavior 4 (2017), 19–43.
  9. User Attitudes towards Algorithmic Opacity and Transparency in Online Reviewing Platforms. 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, 1–14. https://doi.org/10.1145/3290605.3300724
  10. Examining mobility among people living with HIV in rural areas. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. 1–17.
  11. Principled artificial intelligence: Mapping consensus in ethical and rights-based approaches to principles for AI. Berkman Klein Center Research Publication 2020-1 (2020).
  12. Value sensitive design: Theory and methods. University of Washington technical report 2 (2002), 12.
  13. Batya Friedman and Peter H Kahn Jr. 2000. New directions: A value-sensitive design approach to augmented reality. In Proceedings of DARE 2000 on designing augmented reality environments. 163–164.
  14. Ella Glikson and Anita Williams Woolley. 2020. Human trust in artificial intelligence: Review of empirical research. Academy of Management Annals 14, 2 (2020), 627–660.
  15. Designing for labour: uber and the on-demand mobile workforce. In Proceedings of the 2016 CHI conference on human factors in computing systems. 1632–1643.
  16. Privacy-aware dynamic ride sharing. ACM Transactions on Spatial Algorithms and Systems (TSAS) 2, 1 (2016), 1–41.
  17. Saumya Gupta and Theresa Jean Tanenbaum. 2019. Evaluating the Pleasures of Agency in Shiva’s Rangoli, a Tangible Storytelling Installation. In Proceedings of the 2019 on Designing Interactive Systems Conference. 49–60.
  18. AI Hleg. 2019. Ethics guidelines for trustworthy AI. B-1049 Brussels (2019).
  19. The automation of leadership functions: Would people trust decision algorithms? Computers in Human Behavior 116 (2021), 106635.
  20. Incorporating user control in automated interactive scheduling systems. In Proceedings of the 8th ACM Conference on Designing Interactive Systems. 306–309.
  21. Algorithmic anxiety and coping strategies of Airbnb hosts. In Proceedings of the 2018 CHI conference on human factors in computing systems. 1–12.
  22. Support for social and cultural capital development in real-time ridesharing services. In Proceedings of the 2018 CHI conference on human factors in computing systems. 1–12.
  23. René F. Kizilcec. 2016. How Much Information? Effects of Transparency on Trust in an Algorithmic Interface. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (San Jose, California, USA) (CHI ’16). Association for Computing Machinery, New York, NY, USA, 2390–2395. https://doi.org/10.1145/2858036.2858402
  24. Working with machines: The impact of algorithmic and data-driven management on human workers. In Proceedings of the 33rd annual ACM conference on human factors in computing systems. 1603–1612.
  25. Q Vera Liao and Michael Muller. 2019. Enabling Value Sensitive AI Systems through Participatory Design Fictions. arXiv preprint arXiv:1912.07381 (2019).
  26. Mustafa Lokhandwala and Hua Cai. 2018. Dynamic ride sharing using traditional taxis and shared autonomous taxis: A case study of NYC. Transportation Research Part C: Emerging Technologies 97 (2018), 45–60.
  27. Kelin Luo and Frits CR Spieksma. 2022. Minimizing Travel Time and Latency in Multi-Capacity Ride-Sharing Problems. Algorithms 15, 2 (2022), 30.
  28. “Brush it Off”: How Women Workers Manage and Cope with Bias and Harassment in Gender-agnostic Gig Platforms. In CHI Conference on Human Factors in Computing Systems. 1–13.
  29. Using stakeholder theory to examine drivers’ stake in Uber. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. 1–12.
  30. Marije Nouwen and Bieke Zaman. 2018. Redefining the role of parents in young children’s online interactions. A value-sensitive design case study. International Journal of Child-Computer Interaction 18 (2018), 22–26.
  31. Kenya Freeman Oduor and Eric N Wiebe. 2008. The effects of automated decision algorithm modality and transparency on reported trust and task performance. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting, Vol. 52. SAGE Publications Sage CA: Los Angeles, CA, 302–306.
  32. Chad Richards and TC Nicholas Graham. 2016. Developing compelling repetitive-motion exergames by balancing player agency with the constraints of exercise. In Proceedings of the 2016 ACM Conference on Designing Interactive Systems. 911–923.
  33. A reinforcement learning based algorithm for multi-hop ride-sharing: Model-free approach. In Neural Information Processing Systems (Neurips) Workshop.
  34. A distributed model-free algorithm for multi-hop ride-sharing using deep reinforcement learning. IEEE Transactions on Intelligent Transportation Systems (2021).
  35. Zach Singleton. 2022. A peek into your rating. https://www.uber.com/newsroom/rider-ratings-breakdown/
  36. Understanding the cost of driving trips. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. 430–434.
  37. Frontiers in service science: Ride matching for peer-to-peer ride sharing: A review and future directions. Service Science 12, 2-3 (2020), 44–60.
  38. Value sensitive design for autonomous vehicle motion planning. In 2018 IEEE Intelligent Vehicles Symposium (IV). IEEE, 1157–1162.
  39. Steven Umbrello. 2019. Beneficial artificial intelligence coordination by means of a value sensitive design approach. Big Data and Cognitive Computing 3, 1 (2019), 5.
  40. Steven Umbrello and Angelo Frank De Bellis. 2018. A value-sensitive design approach to intelligent agents. Artificial Intelligence Safety and Security (2018) CRC Press (. ed) Roman Yampolskiy (2018).
  41. Designing theory-driven user-centric explainable AI. In Proceedings of the 2019 CHI conference on human factors in computing systems. 1–15.
  42. Understanding the effects of taxi ride-sharing—A case study of Singapore. Computers, Environment and Urban Systems 69 (2018), 124–132.
  43. Till Winkler and Sarah Spiekermann. 2021. Twenty years of value sensitive design: a review of methodological practices in VSD projects. Ethics and Information Technology 23, 1 (2021), 17–21.
  44. Algorithmic management reimagined for workers and by workers: Centering worker well-being in gig work. In CHI Conference on Human Factors in Computing Systems. 1–20.

Summary

No one has generated a summary of this paper yet.

Ai Sparkles Streamline Icon: https://streamlinehq.com Sign Up to Summarize

Paper to Video (Beta)

Whiteboard

No one has generated a whiteboard explanation for this paper yet.

Ai Sparkles Streamline Icon: https://streamlinehq.com Sign Up to Generate

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Ai Sparkles Streamline Icon: https://streamlinehq.com Generate Now

Continue Learning

We haven't generated follow-up questions for this paper yet.

Ai Sparkles Streamline Icon: https://streamlinehq.com Generate Now

Collections

Sign up for free to add this paper to one or more collections.

User Circle Single Streamline Icon: https://streamlinehq.com Sign Up