mlsanityData to 7 Oct 2026

Long-Term Fairness Inquiries and Pursuits in Machine Learning: A Survey of Notions, Methods, and Challenges

arXiv 2406.06736 ↗First posted 10 Jun 2024cs.LG cs.AI cs.CYcited by 4

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Abstract (arXiv)

The widespread integration of Machine Learning systems in daily life, particularly in high-stakes domains, has raised concerns about the fairness implications. While prior works have investigated static fairness measures, recent studies reveal that automated decision-making has long-term implications and that off-the-shelf fairness approaches may not serve the purpose of achieving long-term fairness. Additionally, the existence of feedback loops and the interaction between models and the environment introduces additional complexities that may deviate from the initial fairness goals. In this survey, we review existing literature on long-term fairness from different perspectives and present a taxonomy for long-term fairness studies. We highlight key challenges and consider future research directions, analyzing both current issues and potential further explorations.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 90 of its 136 references that are in the map. First posted on arXiv 10 Jun 2024.

Builds on

90 of 136 references.

References · 90

  1. 2019A Survey on Bias and Fairness in Machine Learningcited by 1,911
  2. 2017Counterfactual Fairnesscited by 802
  3. 2017Deep Reinforcement Learning that Matterscited by 727
  4. 2017Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairnesscited by 381
  5. 2018Fairness Without Demographics in Repeated Loss Minimizationcited by 363
  6. 2018Actionable Recourse in Linear Classificationcited by 327
  7. 2020Performative Predictioncited by 318
  8. 2020Algorithmic Recourse: from Counterfactual Explanations to Interventionscited by 250
  9. 2020Bias and Debias in Recommender System: A Survey and Future Directionscited by 239
  10. 2018A comparative study of fairness-enhancing interventions in machine learningcited by 208
  11. 2017Avoiding Discrimination through Causal Reasoningcited by 191
  12. 2018Delayed Impact of Fair Machine Learningcited by 183
38 more
  1. 2016Fairness in Learning: Classic and Contextual Banditscited by 167
  2. 2021A survey on datasets for fairness-aware machine learningcited by 157
  3. 2017Fairness in Machine Learning: Lessons from Political Philosophycited by 148
  4. 2017Fair Inference On Outcomescited by 143
  5. 2018The Frontiers of Fairness in Machine Learningcited by 139
  6. 2020Algorithmic recourse under imperfect causal knowledge: a probabilistic approachcited by 139
  7. 2021Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Modelscited by 139
  8. 2017Strategic Classification from Revealed Preferencescited by 126
  9. 2018The Social Cost of Strategic Classificationcited by 105
  10. 2017Runaway Feedback Loops in Predictive Policingcited by 97
  11. 2021Outside the Echo Chamber: Optimizing the Performative Riskcited by 95
  12. 2018Fairness Under Unawareness: Assessing Disparity When Protected Class Is Unobservedcited by 94
  13. 2016Fairness in Reinforcement Learningcited by 93
  14. 2020Stochastic Optimization for Performative Predictioncited by 92
  15. 2023Evaluating the Social Impact of Generative AI Systems in Systems and Societycited by 91
  16. 2024RLHF Deciphered: A Critical Analysis of Reinforcement Learning from Human Feedback for LLMscited by 89
  17. 2019Unbiased Recommender Learning from Missing-Not-At-Random Implicit Feedbackcited by 79
  18. 2019Achieving Fairness in the Stochastic Multi-armed Bandit Problemcited by 77
  19. 2021Towards Long-term Fairness in Recommendationcited by 77
  20. 2018The Disparate Effects of Strategic Manipulationcited by 75
  21. 2020On the Fairness of Causal Algorithmic Recoursecited by 69
  22. 2020Controlling Fairness and Bias in Dynamic Learning-to-Rankcited by 67
  23. 2024Causal Representation Learning from Multiple Distributions: A General Settingcited by 67
  24. 2018Online Learning with an Unknown Fairness Metriccited by 61
  25. 2021It's COMPASlicated: The Messy Relationship between RAI Datasets and Algorithmic Fairness Benchmarkscited by 61
  26. 2020Learning Fair Policies in Multiobjective (Deep) Reinforcement Learning with Average and Discounted Rewardscited by 60
  27. 2020How Do Fair Decisions Fare in Long-term Qualification?cited by 59
  28. 2021DynaEval: Unifying Turn and Dialogue Level Evaluationcited by 59
  29. 2021Socially Responsible AI Algorithms: Issues, Purposes, and Challengescited by 56
  30. 2019Algorithms for Fairness in Sequential Decision Makingcited by 53
  31. 2023Performative Prediction: Past and Futurecited by 52
  32. 2019Equalizing Recourse across Groupscited by 51
  33. 2022Latent Hierarchical Causal Structure Discovery with Rank Constraintscited by 50
  34. 2019On the Long-term Impact of Algorithmic Decision Policies: Effort Unfairness and Feature Segregation through Social Learningcited by 48
  35. 2019Causal Modeling for Fairness in Dynamical Systemscited by 46
  36. 2017A Short-term Intervention for Long-term Fairness in the Labor Marketcited by 44
  37. 2018Fairness Under Compositioncited by 43
  38. 2017Calibrated Fairness in Banditscited by 42

50 most cited of 90 All 90 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 2; 2026: 1.

4 papers.

  1. 2024Different Horses for Different Courses: Comparing Bias Mitigation Algorithms in MLcited by 3
  2. 2025FairSense: Long-Term Fairness Analysis of ML-Enabled Systemscited by 3
  3. 2025Evolutionary Prediction Gamescited by 0
  4. 2026Long-term Fairness with Selective Labelscited by 0