mlsanityData to 7 Oct 2026

Fairlearn: Assessing and Improving Fairness of AI Systems

arXiv 2303.16626 ↗First posted 29 Mar 2023cs.LG cs.AI cs.CYcited by 74

Not on the map. Why?

Abstract (arXiv)

Fairlearn is an open source project to help practitioners assess and improve fairness of artificial intelligence (AI) systems. The associated Python library, also named fairlearn, supports evaluation of a model's output across affected populations and includes several algorithms for mitigating fairness issues. Grounded in the understanding that fairness is a sociotechnical challenge, the project integrates learning resources that aid practitioners in considering a system's broader societal context.

Key facts. Cited by 74 papers in the map (data through 7 Oct 2026). Builds on 12 of its 37 references that are in the map. First posted on arXiv 29 Mar 2023.

Builds on

12 of 37 references.

References · 12

  1. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  2. 2016Equality of Opportunity in Supervised Learningcited by 2,000
  3. 2020Language (Technology) is Power: A Critical Survey of "Bias" in NLPcited by 951
  4. 2018Mitigating Unwanted Biases with Adversarial Learningcited by 663
  5. 2018A Reductions Approach to Fair Classificationcited by 585
  6. 2019Measurement and Fairnesscited by 299
  7. 2018Improving fairness in machine learning systems: What do industry practitioners need?cited by 262
  8. 2019Fair Regression: Quantitative Definitions and Reduction-based Algorithmscited by 168
  9. 2021Designing Disaggregated Evaluations of AI Systems: Choices, Considerations, and Tradeoffscited by 48
  10. 2022The four-fifths rule is not disparate impact: a woeful tale of epistemic trespassing in algorithmic fairnesscited by 21
  11. 2019On the Legal Compatibility of Fairness Definitionscited by 19
  12. 2021The Contestation of Tech Ethics: A Sociotechnical Approach to Technology Ethics in Practicecited by 12

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 11; 2024: 17; 2025: 31; 2026: 15.

74 papers.

Sort:

By area:

  1. 2023Adversarial attacks and defenses in explainable artificial intelligence: A surveycited by 47
  2. 2024PyRIT: A Framework for Security Risk Identification and Red Teaming in Generative AI Systemcited by 29
  3. 2024Farsight: Fostering Responsible AI Awareness During AI Application Prototypingcited by 28
  4. 2023FairTune: Optimizing Parameter Efficient Fine Tuning for Fairness in Medical Image Analysiscited by 23
  5. 2023One Model Many Scores: Using Multiverse Analysis to Prevent Fairness Hacking and Evaluate the Influence of Model Design Decisionscited by 12
  6. 2024OxonFair: A Flexible Toolkit for Algorithmic Fairnesscited by 12
  7. 2023A Sequentially Fair Mechanism for Multiple Sensitive Attributescited by 8
  8. 2024A structured regression approach for evaluating model performance across intersectional subgroupscited by 8
  9. 2024ABCFair: an Adaptable Benchmark approach for Comparing Fairness Methodscited by 8
  10. 2023Positivity-free Policy Learning with Observational Datacited by 6
  11. 2023Mining bias-target Alignment from Voronoi Cellscited by 5
  12. 2024Unlawful Proxy Discrimination: A Framework for Challenging Inherently Discriminatory Algorithmscited by 5
38 more
  1. 2024EARN Fairness: Explaining, Asking, Reviewing, and Negotiating Artificial Intelligence Fairness Metrics Among Stakeholderscited by 5
  2. 2025LangFair: A Python Package for Assessing Bias and Fairness in Large Language Model Use Casescited by 5
  3. 2023Survey on AI Ethics: A Socio-technical Perspectivecited by 4
  4. 2025Revisiting Pre-processing Group Fairness: A Modular Benchmarking Frameworkcited by 4
  5. 2023Human-in-the-loop Fairness: Integrating Stakeholder Feedback to Incorporate Fairness Perspectives in Responsible AIcited by 3
  6. 2024The Life Cycle of Large Language Models: A Review of Biases in Educationcited by 3
  7. 2024Trustworthy and Responsible AI for Human-Centric Autonomous Decision-Making Systemscited by 3
  8. 2024FairFML: Fair Federated Machine Learning with a Case Study on Reducing Gender Disparities in Cardiac Arrest Outcome Predictioncited by 3
  9. 2025Advancing Responsible Innovation in Agentic AI: A study of Ethical Frameworks for Household Automationcited by 3
  10. 2023Fair Enough? A map of the current limitations of the requirements to have fair algorithmscited by 2
  11. 2024FairX: A comprehensive benchmarking tool for model analysis using fairness, utility, and explainabilitycited by 2
  12. 2024Cherry on the Cake: Fairness is NOT an Optimization Problemcited by 2
  13. 2024Feasibility of Detecting Cognitive Impairment and Psychological Well-being among Older Adults Using Facial, Acoustic, Linguistic, and Cardiovascular Patterns Derived from Remote Conversationscited by 2
  14. 2025Evidence for Phenotype-Driven Disparities in Freezing of Gait Detection and Approaches to Bias Mitigationcited by 2
  15. 2025Advances in LLMs with Focus on Reasoning, Adaptability, Efficiency and Ethicscited by 2
  16. 2025Bias Begins with Data: The FairGround Corpus for Robust and Reproducible Research on Algorithmic Fairnesscited by 2
  17. 2026FairLogue: A Toolkit for Intersectional Fairness Analysis in Clinical Machine Learning Modelscited by 2
  18. 2023Simulating counterfactualscited by 1
  19. 2023Rethinking Algorithmic Fairness for Human-AI Collaborationcited by 1
  20. 2024SureMap: Simultaneous Mean Estimation for Single-Task and Multi-Task Disaggregated Evaluationcited by 1
  21. 2025A Multi-Objective Evaluation Framework for Analyzing Utility-Fairness Trade-Offs in Machine Learning Systemscited by 1
  22. 2025Fairmetrics: An R package for group fairness evaluationcited by 1
  23. 2025Size-adaptive Hypothesis Testing for Fairnesscited by 1
  24. 2025Measurement as Bricolage: Examining How Data Scientists Construct Target Variables for Predictive Modeling Taskscited by 1
  25. 2025FairTabGen: High-Fidelity and Fair Synthetic Health Data Generation from Limited Samplescited by 1
  26. 2025JustEva: A Toolkit to Evaluate LLM Fairness in Legal Knowledge Inferencecited by 1
  27. 2025Amulet: a Python Library for Assessing Interactions Among ML Defenses and Riskscited by 1
  28. 2025RAISE: A Unified Framework for Responsible AI Scoring and Evaluationcited by 1
  29. 2025A multimodal Bayesian Network for symptom-level depression and anxiety prediction from voice and speech datacited by 1
  30. 2026RISED: A Pre-Deployment Evaluation Framework for High-Stakes AI Decision-Support Systems, with Application to Healthcarecited by 1
  31. 2024Advancing Explainable AI Toward Human-Like Intelligence: Forging the Path to Artificial Braincited by 0
  32. 2024Data Quality in Edge Machine Learning: A State-of-the-Art Surveycited by 0
  33. 2024Fair4Free: Generating High-fidelity Fair Synthetic Samples using Data Free Distillationcited by 0
  34. 2025Fairness-Aware Low-Rank Representation Fine-Tuningcited by 0
  35. 2025EquiPy: Sequential Fairness using Optimal Transport in Pythoncited by 0
  36. 2025seeBias: A Comprehensive Tool for Assessing and Visualizing AI Fairnesscited by 0
  37. 2025FairSHAP: Preprocessing for Fairness Through Attribution-Based Data Augmentationcited by 0
  38. 2025Simulating Biases for Interpretable Fairness in Offline and Online Classifierscited by 0

50 most cited of 74 All 74 (JSON)