mlsanityData to 7 Oct 2026

From Parity to Preference-based Notions of Fairness in Classification

arXiv 1707.00010 ↗First posted 30 Jun 2017stat.ML cs.LGcited by 60

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Abstract (arXiv)

The adoption of automated, data-driven decision making in an ever expanding range of applications has raised concerns about its potential unfairness towards certain social groups. In this context, a number of recent studies have focused on defining, detecting, and removing unfairness from data-driven decision systems. However, the existing notions of fairness, based on parity (equality) in treatment or outcomes for different social groups, tend to be quite stringent, limiting the overall decision making accuracy. In this paper, we draw inspiration from the fair-division and envy-freeness literature in economics and game theory and propose preference-based notions of fairness -- given the choice between various sets of decision treatments or outcomes, any group of users would collectively prefer its treatment or outcomes, regardless of the (dis)parity as compared to the other groups. Then, we introduce tractable proxies to design margin-based classifiers that satisfy these preference-based notions of fairness. Finally, we experiment with a variety of synthetic and real-world datasets and show that preference-based fairness allows for greater decision accuracy than parity-based fairness.

Key facts. Cited by 60 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 Jun 2017.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 16; 2022: 18; 2023: 9; 2024: 5; 2025: 6; 2026: 6.

60 papers.

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  1. 2021Towards a Unified Framework for Fair and Stable Graph Representation Learningcited by 128
  2. 2022Bias Mitigation for Machine Learning Classifiers: A Comprehensive Surveycited by 125
  3. 2021Improving Fairness via Federated Learningcited by 39
  4. 2022Causal Conceptions of Fairness and their Consequencescited by 38
  5. 2021Fairness Perceptions of Algorithmic Decision-Making: A Systematic Review of the Empirical Literaturecited by 27
  6. 2021Fairness without Imputation: A Decision Tree Approach for Fair Prediction with Missing Valuescited by 24
  7. 2021A Sociotechnical View of Algorithmic Fairnesscited by 24
  8. 2022Marrying Fairness and Explainability in Supervised Learningcited by 23
  9. 2021Online certification of preference-based fairness for personalized recommender systemscited by 22
  10. 2025Position is Power: System Prompts as a Mechanism of Bias in Large Language Models (LLMs)cited by 19
  11. 2021Loss-Aversively Fair Classificationcited by 18
  12. 2021Unintended Selection: Persistent Qualification Rate Disparities and Interventionscited by 18
38 more
  1. 2022Adaptive Sampling Strategies to Construct Equitable Training Datasetscited by 18
  2. 2022FairEdit: Preserving Fairness in Graph Neural Networks through Greedy Graph Editingcited by 14
  3. 2021Through the Data Management Lens: Experimental Analysis and Evaluation of Fair Classificationcited by 13
  4. 2022Equal Improvability: A New Fairness Notion Considering the Long-term Impactcited by 13
  5. 2023Counterfactually Fair Representationcited by 9
  6. 2021Pareto Efficient Fairness in Supervised Learning: From Extraction to Tracingcited by 8
  7. 2022Multi-disciplinary fairness considerations in machine learning for clinical trialscited by 8
  8. 2023Understanding Fairness Surrogate Functions in Algorithmic Fairnesscited by 8
  9. 2022Fairness Implications of Encoding Protected Categorical Attributescited by 7
  10. 2022What is Proxy Discrimination?cited by 7
  11. 2023Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda for Developing Practical Guidelines and Toolscited by 7
  12. 2023Balancing Act: Constraining Disparate Impact in Sparse Modelscited by 7
  13. 2021Fairness for Robust Learning to Rankcited by 6
  14. 2022When Personalization Harms: Reconsidering the Use of Group Attributes in Predictioncited by 6
  15. 2023Towards Fairness in Personalized Ads Using Impression Variance Aware Reinforcement Learningcited by 6
  16. 2021Impact of Data Processing on Fairness in Supervised Learningcited by 5
  17. 2021Adversarial Regression with Doubly Non-negative Weighting Matricescited by 5
  18. 2022Measuring Fairness of Text Classifiers via Prediction Sensitivitycited by 5
  19. 2022FairRoad: Achieving Fairness for Recommender Systems with Optimized Antidote Datacited by 5
  20. 2023Participatory Personalization in Classificationcited by 5
  21. 2022Fast Feature Selection with Fairness Constraintscited by 4
  22. 2022Towards Fairness-Aware Multi-Objective Optimizationcited by 4
  23. 2024Striking a Balance in Fairness for Dynamic Systems Through Reinforcement Learningcited by 4
  24. 2021Fairness-aware Summarization for Justified Decision-Makingcited by 3
  25. 2022Distributive Justice as the Foundational Premise of Fair ML: Unification, Extension, and Interpretation of Group Fairness Metricscited by 3
  26. 2024Referee-Meta-Learning for Fast Adaptation of Locational Fairnesscited by 3
  27. 2022How Robust is your Fair Model? Exploring the Robustness of Diverse Fairness Strategiescited by 2
  28. 2022Efficient Classification with Counterfactual Reasoning and Active Learningcited by 2
  29. 2023Designing Equitable Algorithmscited by 2
  30. 2024FairLoRA: Unpacking Bias Mitigation in Vision Models with Fairness-Driven Low-Rank Adaptationcited by 2
  31. 2026Learning Fair Pareto-Optimal Policies in Multi-Objective Reinforcement Learningcited by 2
  32. 2023Dr. FERMI: A Stochastic Distributionally Robust Fair Empirical Risk Minimization Frameworkcited by 1
  33. 2024Scalable Algorithms for Individual Preference Stable Clusteringcited by 1
  34. 2025Fairness-aware Anomaly Detection via Fair Projectioncited by 1
  35. 2025Algorithmic Hiring and Diversity: Reducing Human-Algorithm Similarity for Better Outcomescited by 1
  36. 2025Demographic-Agnostic Fairness without Harmcited by 1
  37. 2025Achieving Fairness Without Harm via Selective Demographic Expertscited by 1
  38. 2025On the Role of Calibration in Benchmarking Algorithmic Fairness for Skin Cancer Detectioncited by 1

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