mlsanityData to 14 Oct 2026

How Do Fairness Definitions Fare? Examining Public Attitudes Towards Algorithmic Definitions of Fairness

arXiv 1811.03654 ↗First posted 8 Nov 2018cs.AI cs.CYcited by 48

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Abstract (arXiv)

What is the best way to define algorithmic fairness? While many definitions of fairness have been proposed in the computer science literature, there is no clear agreement over a particular definition. In this work, we investigate ordinary people's perceptions of three of these fairness definitions. Across two online experiments, we test which definitions people perceive to be the fairest in the context of loan decisions, and whether fairness perceptions change with the addition of sensitive information (i.e., race of the loan applicants). Overall, one definition (calibrated fairness) tends to be more preferred than the others, and the results also provide support for the principle of affirmative action.

Key facts. Cited by 48 papers in the map (data through 14 Oct 2026). First posted on arXiv 8 Nov 2018.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 11; 2022: 12; 2023: 7; 2024: 7; 2025: 7; 2026: 4.

48 papers.

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  1. 2022Training Data Influence Analysis and Estimation: A Surveycited by 135
  2. 2021Trustworthy AI: A Computational Perspectivecited by 93
  3. 2022Trustworthy Graph Neural Networks: Aspects, Methods and Trendscited by 89
  4. 2021FairDrop: Biased Edge Dropout for Enhancing Fairness in Graph Representation Learningcited by 68
  5. 2022How Different Groups Prioritize Ethical Values for Responsible AIcited by 49
  6. 2021Fairness Perceptions of Algorithmic Decision-Making: A Systematic Review of the Empirical Literaturecited by 27
  7. 2022Aligning Eyes between Humans and Deep Neural Network through Interactive Attention Alignmentcited by 27
  8. 2021Human Perceptions on Moral Responsibility of AI: A Case Study in AI-Assisted Bail Decision-Makingcited by 23
  9. 2021Responsible AI: Gender bias assessment in emotion recognitioncited by 22
  10. 2021PreferenceNet: Encoding Human Preferences in Auction Design with Deep Learningcited by 22
  11. 2022"There Is Not Enough Information": On the Effects of Explanations on Perceptions of Informational Fairness and Trustworthiness in Automated Decision-Makingcited by 19
  12. 2022What-is and How-to for Fairness in Machine Learning: A Survey, Reflection, and Perspectivecited by 18
36 more
  1. 2021Explainability Is in the Mind of the Beholder: Establishing the Foundations of Explainable Artificial Intelligencecited by 13
  2. 2024The Pursuit of Fairness in Artificial Intelligence Models: A Surveycited by 13
  3. 2022Towards Involving End-users in Interactive Human-in-the-loop AI Fairnesscited by 12
  4. 2021Fairness and Transparency in Recommendation: The Users' Perspectivecited by 10
  5. 2023Fairness Evaluation in Text Classification: Machine Learning Practitioner Perspectives of Individual and Group Fairnesscited by 7
  6. 2024Underneath the Numbers: Quantitative and Qualitative Gender Fairness in LLMs for Depression Predictioncited by 6
  7. 2024EARN Fairness: Explaining, Asking, Reviewing, and Negotiating Artificial Intelligence Fairness Metrics Among Stakeholderscited by 5
  8. 2022Towards Fairness-Aware Multi-Objective Optimizationcited by 4
  9. 2022Towards Trustworthy AI-Empowered Real-Time Bidding for Online Advertisement Auctioningcited by 4
  10. 2023Retiring DeltaDP: New Distribution-Level Metrics for Demographic Paritycited by 4
  11. 2022The Fairness Field Guide: Perspectives from Social and Formal Sciencescited by 3
  12. 2023Procedural Fairness Through Decoupling Objectionable Data Generating Componentscited by 3
  13. 2023Drop Edges and Adapt: a Fairness Enforcing Fine-tuning for Graph Neural Networkscited by 2
  14. 2023Consumer-side Fairness in Recommender Systems: A Systematic Survey of Methods and Evaluationcited by 2
  15. 2024Enhancing Fairness and Performance in Machine Learning Models: A Multi-Task Learning Approach with Monte-Carlo Dropout and Pareto Optimalitycited by 2
  16. 2021The FairCeptron: A Framework for Measuring Human Perceptions of Algorithmic Fairnesscited by 1
  17. 2023Trustworthy Representation Learning Across Domainscited by 1
  18. 2024Understanding Decision Subjects' Engagement with and Perceived Fairness of AI Models When Opportunities of Qualification Improvement Existcited by 1
  19. 2024FAIREDU: A Multiple Regression-Based Method for Enhancing Fairness in Machine Learning Models for Educational Applicationscited by 1
  20. 2025Fairness in Federated Learning: Fairness for Whom?cited by 1
  21. 2026Who Defines Fairness? Target-Based Prompting for Demographic Representation in Generative Modelscited by 1
  22. 2021Descriptive AI Ethics: Collecting and Understanding the Public Opinioncited by 0
  23. 2021Non-Comparative Fairness for Human-Auditing and Its Relation to Traditional Fairness Notionscited by 0
  24. 2022On Learning and Enforcing Latent Assessment Models using Binary Feedback from Human Auditors Regarding Black-Box Classifierscited by 0
  25. 2022Tensions Between the Proxies of Human Values in AIcited by 0
  26. 2023Reflective Hybrid Intelligence for Meaningful Human Control in Decision-Support Systemscited by 0
  27. 2024Understanding Fairness in Recommender Systems: A Healthcare Perspectivecited by 0
  28. 2025Laypeople's Attitudes Towards Fair, Affirmative, and Discriminatory Decision-Making Algorithmscited by 0
  29. 2025Which Demographic Features Are Relevant for Individual Fairness Evaluation of U.S. Recidivism Risk Assessment Tools?cited by 0
  30. 2025Effort-aware Fairness: Incorporating a Philosophy-informed, Human-centered Notion of Effort into Algorithmic Fairness Metricscited by 0
  31. 2025Perception-Driven Bias Detection in Machine Learning via Crowdsourced Visual Judgmentcited by 0
  32. 2025Cost-Free Personalization via Information-Geometric Projection in Bayesian Federated Learningcited by 0
  33. 2025"I think this is fair": Uncovering the Complexities of Stakeholder Decision-Making in AI Fairness Assessmentcited by 0
  34. 2026Empowering Affected Individuals to Shape AI Fairness Assessments: Processes, Criteria, and Toolscited by 0
  35. 2026Fairness of Classifiers in the Presence of Constraints between Featurescited by 0
  36. 2026Examining Agents' Bias Amplification versus Suppression in Multi-Agent Systemscited by 0