Algorithmic Mediation in Group Decisions: Fairness Perceptions of Algorithmically Mediated vs. Discussion-Based Social Division
Abstract
How do individuals perceive algorithmic vs. group-made decisions? We investigated people's perceptions of mathematically-proven fair division algorithms making social division decisions. In our first qualitative study, about one third of the participants perceived algorithmic decisions as less than fair (30% for self, 36% for group), often because algorithmic assumptions about users did not account for multiple concepts of fairness or social behaviors, and the process of quantifying preferences through interfaces was prone to error. In our second experiment, algorithmic decisions were perceived to be less fair than discussion-based decisions, dependent on participants' interpersonal power and computer programming knowledge. Our work suggests that for algorithmic mediation to be fair, algorithms and their interfaces should account for social and altruistic behaviors that may be difficult to define in mathematical terms.
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Prior research suggests that increased transparency in AI systems can have the overall effect of improving trust rather than diminishing it, at least when paired with corresponding, meaningful options for user control.
“Prior research suggests that increased transparency in AI systems can have the overall effect of improving trust rather than diminishing it, at least when paired with corresponding, meaningful options for user control”
From Equity and Artificial Intelligence in Education: Will "AIEd" Amplify or Alleviate Inequities in Education? (2021) · cites this paper as Lee & Baykal, 2017
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- Authors
- Lee, M. K., & Baykal, S.
- Affiliations
- Carnegie Mellon University (US)
- Google (United States) (US)
- ORCID
- Lee, Min Kyung
- Venue
- Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing
- Publisher
- ACM
- Published
- 2017-02-25
- Pages
- 1035-1048
- OpenAlex
- W2588194244
- Cited by
- 182
- References
- 4
- Citations by year
- 2026: 10 · 2025: 16 · 2024: 22 · 2023: 21 · 2022: 26 · 2021: 29 · 2020: 22 · 2019: 22 · 2018: 11 · 2017: 2 · 2016: 1
- FWCI
- 38.87
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- ACM Conference on Computer Supported Cooperative Work (CSCW) (publishedVersion)
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Game Theory and Voting Systems
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Keywords
- algorithmic mediation, fair division, perceived fairness, group decision making, social division, interpersonal power, programming knowledge, altruism, preference elicitation
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