mlsanityData to 7 Oct 2026

Auditing ML Models for Individual Bias and Unfairness

arXiv 2003.05048 ↗First posted 11 Mar 2020stat.ML cs.LGcited by 18

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Abstract (arXiv)

We consider the task of auditing ML models for individual bias/unfairness. We formalize the task in an optimization problem and develop a suite of inferential tools for the optimal value. Our tools permit us to obtain asymptotic confidence intervals and hypothesis tests that cover the target/control the Type I error rate exactly. To demonstrate the utility of our tools, we use them to reveal the gender and racial biases in Northpointe's COMPAS recidivism prediction instrument.

Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Mar 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 4; 2022: 2; 2023: 4; 2024: 3; 2025: 4; 2026: 1.

18 papers.

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  1. 2021Testing Group Fairness via Optimal Transport Projectionscited by 23
  2. 2023Statistical Inference for Fairness Auditingcited by 19
  3. 2024From Transparency to Accountability and Back: A Discussion of Access and Evidence in AI Auditingcited by 15
  4. 2021Statistical inference for individual fairnesscited by 13
  5. 2024PROSAC: Provably Safe Certification for Machine Learning Models under Adversarial Attackscited by 11
  6. 2022An External Stability Audit Framework to Test the Validity of Personality Prediction in AI Hiringcited by 10
  7. 2023Racial Bias within Face Recognition: A Surveycited by 9
  8. 2025TeleSparse: Practical Privacy-Preserving Verification of Deep Neural Networkscited by 9
  9. 2023Fairness Evaluation in Text Classification: Machine Learning Practitioner Perspectives of Individual and Group Fairnesscited by 7
  10. 2023Is this model reliable for everyone? Testing for strong calibrationcited by 6
  11. 2021Everything is Relative: Understanding Fairness with Optimal Transportcited by 2
  12. 2021Fair Representation Learning using Interpolation Enabled Disentanglementcited by 1
6 more
  1. 2022Fair mappingcited by 0
  2. 2024Peer-induced Fairness: A Causal Approach for Algorithmic Fairness Auditingcited by 0
  3. 2025From Fragile to Certified: Wasserstein Audits of Group Fairness Under Distribution Shiftcited by 0
  4. 2025Cost Efficient Fairness Audit Under Partial Feedbackcited by 0
  5. 2025Wasserstein projection distance for fairness testing of regression modelscited by 0
  6. 2026A Geometric Theory of Robust Fairness Auditscited by 0