mlsanityData to 7 Oct 2026

On the Legal Compatibility of Fairness Definitions

arXiv 1912.00761 ↗First posted 25 Nov 2019cs.CY cs.AI cs.LGcited by 19

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Abstract (arXiv)

Past literature has been effective in demonstrating ideological gaps in machine learning (ML) fairness definitions when considering their use in complex socio-technical systems. However, we go further to demonstrate that these definitions often misunderstand the legal concepts from which they purport to be inspired, and consequently inappropriately co-opt legal language. In this paper, we demonstrate examples of this misalignment and discuss the differences in ML terminology and their legal counterparts, as well as what both the legal and ML fairness communities can learn from these tensions. We focus this paper on U.S. anti-discrimination law since the ML fairness research community regularly references terms from this body of law.

Key facts. Cited by 19 papers in the map (data through 7 Oct 2026). First posted on arXiv 25 Nov 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 3; 2022: 6; 2023: 5; 2024: 2; 2025: 2; 2026: 1.

19 papers.

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  1. 2021Re-imagining Algorithmic Fairness in India and Beyondcited by 102
  2. 2023Fairlearn: Assessing and Improving Fairness of AI Systemscited by 74
  3. 2021Just What do You Think You're Doing, Dave?' A Checklist for Responsible Data Use in NLPcited by 47
  4. 2022The four-fifths rule is not disparate impact: a woeful tale of epistemic trespassing in algorithmic fairnesscited by 21
  5. 2021A Framework for Fairness: A Systematic Review of Existing Fair AI Solutionscited by 18
  6. 2022System Cards for AI-Based Decision-Making for Public Policycited by 11
  7. 2022Fairness and Bias in Robot Learningcited by 10
  8. 2024Interpretability Needs a New Paradigmcited by 10
  9. 2023Disentangling and Operationalizing AI Fairness at LinkedIncited by 7
  10. 2023Rating Sentiment Analysis Systems for Bias through a Causal Lenscited by 6
  11. 2023Advances in Automatically Rating the Trustworthiness of Text Processing Servicescited by 6
  12. 2022The Fairness Field Guide: Perspectives from Social and Formal Sciencescited by 3
7 more
  1. 2023The Ethics of AI Value Chainscited by 3
  2. 2025Gender Bias in Explainability: Investigating Performance Disparity in Post-hoc Methodscited by 3
  3. 2022Fairness and Explainability in Automatic Decision-Making Systems. A challenge for computer science and lawcited by 2
  4. 2024REFRESH: Responsible and Efficient Feature Reselection Guided by SHAP Valuescited by 1
  5. 2025Evaluating Fairness and Mitigating Bias in Machine Learning: A Novel Technique using Tensor Data and Bayesian Regressioncited by 1
  6. 2022Walk a Mile in Their Shoes: a New Fairness Criterion for Machine Learningcited by 0
  7. 2026Operationalizing Fairness: Post-Hoc Threshold Optimization Under Hard Resource Limitscited by 0