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The Frontiers of Fairness in Machine Learning

arXiv 1810.08810 ↗First posted 20 Oct 2018cs.LG cs.DS cs.GTcited by 139

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Abstract (arXiv)

The last few years have seen an explosion of academic and popular interest in algorithmic fairness. Despite this interest and the volume and velocity of work that has been produced recently, the fundamental science of fairness in machine learning is still in a nascent state. In March 2018, we convened a group of experts as part of a CCC visioning workshop to assess the state of the field, and distill the most promising research directions going forward. This report summarizes the findings of that workshop. Along the way, it surveys recent theoretical work in the field and points towards promising directions for research.

Key facts. Cited by 139 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Oct 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 38; 2022: 33; 2023: 31; 2024: 22; 2025: 13; 2026: 2.

139 papers.

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  1. 2021Ethical and social risks of harm from Language Modelscited by 957
  2. 2022Bias Mitigation for Machine Learning Classifiers: A Comprehensive Surveycited by 125
  3. 2021A Clarification of the Nuances in the Fairness Metrics Landscapecited by 98
  4. 2023Bias Testing and Mitigation in LLM-based Code Generationcited by 53
  5. 2021Machine Learning in the Search for New Fundamental Physicscited by 50
  6. 2021Unsupervised Learning of Debiased Representations with Pseudo-Attributescited by 44
  7. 2022The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanationscited by 41
  8. 2021Your fairness may vary: Pretrained language model fairness in toxic text classificationcited by 38
  9. 2021Improved Approximation Algorithms for Individually Fair Clusteringcited by 33
  10. 2022Fairness Reprogrammingcited by 33
  11. 2022A Comprehensive Survey on Trustworthy Recommender Systemscited by 32
  12. 2023Understanding Frontline Workers' and Unhoused Individuals' Perspectives on AI Used in Homeless Servicescited by 29
38 more
  1. 2022Aligning Eyes between Humans and Deep Neural Network through Interactive Attention Alignmentcited by 27
  2. 2022Fairness in Recommendation: Foundations, Methods and Applicationscited by 27
  3. 2023Privacy and Fairness in Federated Learning: on the Perspective of Trade-offcited by 26
  4. 2023On The Impact of Machine Learning Randomness on Group Fairnesscited by 26
  5. 2021Approximation Algorithms for Socially Fair Clusteringcited by 25
  6. 2021A Sociotechnical View of Algorithmic Fairnesscited by 24
  7. 2023Consensus and Subjectivity of Skin Tone Annotation for ML Fairnesscited by 22
  8. 2021Strategic Rankingcited by 21
  9. 2022Group Property Inference Attacks Against Graph Neural Networkscited by 21
  10. 2021Deep Clustering based Fair Outlier Detectioncited by 19
  11. 2024CEB: Compositional Evaluation Benchmark for Fairness in Large Language Modelscited by 17
  12. 2021Can Explainable AI Explain Unfairness? A Framework for Evaluating Explainable AIcited by 16
  13. 2022Scalable Spectral Clustering with Group Fairness Constraintscited by 16
  14. 2022Bugs in Machine Learning-based Systems: A Faultload Benchmarkcited by 15
  15. 2024From Transparency to Accountability and Back: A Discussion of Access and Evidence in AI Auditingcited by 15
  16. 2021Deep Exploration for Recommendation Systemscited by 14
  17. 2021Toward Annotator Group Bias in Crowdsourcingcited by 14
  18. 2022Fairness Score and Process Standardization: Framework for Fairness Certification in Artificial Intelligence Systemscited by 14
  19. 2023Learning for Counterfactual Fairness from Observational Datacited by 13
  20. 2021Individually Fair Gradient Boostingcited by 12
  21. 2021Cohort Shapley value for algorithmic fairnesscited by 12
  22. 2022Fair Data Representation for Machine Learning at the Pareto Frontiercited by 12
  23. 2023A Classification of Feedback Loops and Their Relation to Biases in Automated Decision-Making Systemscited by 12
  24. 2021From Learning to Relearning: A Framework for Diminishing Bias in Social Robot Navigationcited by 11
  25. 2021Robustness Disparities in Commercial Face Detectioncited by 11
  26. 2021Learning to be Fair: A Consequentialist Approach to Equitable Decision-Makingcited by 11
  27. 2022Is Fairness Only Metric Deep? Evaluating and Addressing Subgroup Gaps in Deep Metric Learningcited by 11
  28. 2021Fairness-Aware Unsupervised Feature Selectioncited by 10
  29. 2022PosePipe: Open-Source Human Pose Estimation Pipeline for Clinical Researchcited by 10
  30. 2022To the Fairness Frontier and Beyond: Identifying, Quantifying, and Optimizing the Fairness-Accuracy Pareto Frontiercited by 10
  31. 2022Fairness-aware Model-agnostic Positive and Unlabeled Learningcited by 10
  32. 2023FairSISA: Ensemble Post-Processing to Improve Fairness of Unlearning in LLMscited by 10
  33. 2023An Empirical Analysis of Fairness Notions under Differential Privacycited by 9
  34. 2021BeFair: Addressing Fairness in the Banking Sectorcited by 8
  35. 2021Cooperative Multi-Agent Fairness and Equivariant Policiescited by 8
  36. 2021Comparing Human and Machine Bias in Face Recognitioncited by 8
  37. 2021Fairness in Missing Data Imputationcited by 8
  38. 2022Tiny, always-on and fragile: Bias propagation through design choices in on-device machine learning workflowscited by 8

50 most cited of 139 All 139 (JSON)