mlsanityData to 7 Oct 2026

A Survey on Intersectional Fairness in Machine Learning: Notions, Mitigation, and Challenges

arXiv 2305.06969 ↗First posted 11 May 2023cs.LG cs.CYcited by 41

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Abstract (arXiv)

The widespread adoption of Machine Learning systems, especially in more decision-critical applications such as criminal sentencing and bank loans, has led to increased concerns about fairness implications. Algorithms and metrics have been developed to mitigate and measure these discriminations. More recently, works have identified a more challenging form of bias called intersectional bias, which encompasses multiple sensitive attributes, such as race and gender, together. In this survey, we review the state-of-the-art in intersectional fairness. We present a taxonomy for intersectional notions of fairness and mitigation. Finally, we identify the key challenges and provide researchers with guidelines for future directions.

Key facts. Cited by 41 papers in the map (data through 7 Oct 2026). Builds on 45 of its 95 references that are in the map. First posted on arXiv 11 May 2023.

Builds on

45 of 95 references.

References · 45

  1. 2014Deep Learning Face Attributes in the Wildcited by 3,679
  2. 2016Equality of Opportunity in Supervised Learningcited by 2,000
  3. 2019A Survey on Bias and Fairness in Machine Learningcited by 1,911
  4. 2017Counterfactual Fairnesscited by 802
  5. 2018A Reductions Approach to Fair Classificationcited by 585
  6. 2017Age Progression/Regression by Conditional Adversarial Autoencodercited by 426
  7. 2017Algorithmic decision making and the cost of fairnesscited by 402
  8. 2019On Measuring Social Biases in Sentence Encoderscited by 397
  9. 2017Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairnesscited by 381
  10. 2020Fairness in Machine Learning: A Surveycited by 369
  11. 2018Fairness Without Demographics in Repeated Loss Minimizationcited by 363
  12. 2020Fairness without Demographics through Adversarially Reweighted Learningcited by 251
33 more
  1. 2018Examining Gender and Race Bias in Two Hundred Sentiment Analysis Systemscited by 234
  2. 2018Multiaccuracy: Black-Box Post-Processing for Fairness in Classificationcited by 221
  3. 2020Detecting Emergent Intersectional Biases: Contextualized Word Embeddings Contain a Distribution of Human-like Biasescited by 167
  4. 2021Bias Out-of-the-Box: An Empirical Analysis of Intersectional Occupational Biases in Popular Generative Language Modelscited by 141
  5. 2019Assessing Social and Intersectional Biases in Contextualized Word Representationscited by 134
  6. 2018An Intersectional Definition of Fairnesscited by 126
  7. 2019Compositional Fairness Constraints for Graph Embeddingscited by 126
  8. 2020Image Representations Learned With Unsupervised Pre-Training Contain Human-like Biasescited by 107
  9. 2019FairVis: Visual Analytics for Discovering Intersectional Bias in Machine Learningcited by 93
  10. 2018Online Learning with an Unknown Fairness Metriccited by 61
  11. 2022Fairness Testing: A Comprehensive Survey and Analysis of Trendscited by 61
  12. 2022Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluationcited by 59
  13. 2021Socially Responsible AI Algorithms: Issues, Purposes, and Challengescited by 56
  14. 2018Fairness Through Computationally-Bounded Awarenesscited by 55
  15. 2022Low-Degree Multicalibrationcited by 44
  16. 2020Multilingual Twitter Corpus and Baselines for Evaluating Demographic Bias in Hate Speech Recognitioncited by 43
  17. 2021Characterizing Intersectional Group Fairness with Worst-Case Comparisonscited by 42
  18. 2020PANDORA Talks: Personality and Demographics on Redditcited by 40
  19. 2022On Learning Fairness and Accuracy on Multiple Subgroupscited by 31
  20. 2021Evaluating Debiasing Techniques for Intersectional Biasescited by 30
  21. 2021Unpacking the Interdependent Systems of Discrimination: Ableist Bias in NLP Systems through an Intersectional Lenscited by 30
  22. 2018Probably Approximately Metric-Fair Learningcited by 29
  23. 2019Auditing and Achieving Intersectional Fairness in Classification Problemscited by 25
  24. 2018Bayesian Modeling of Intersectional Fairness: The Variance of Biascited by 23
  25. 2022Towards Understanding Fairness and its Composition in Ensemble Machine Learningcited by 17
  26. 2021InfoFair: Information-Theoretic Intersectional Fairnesscited by 15
  27. 2022Mapping the Multilingual Margins: Intersectional Biases of Sentiment Analysis Systems in English, Spanish, and Arabiccited by 13
  28. 2020Causal intersectionality for fair rankingcited by 12
  29. 2022Bounding and Approximating Intersectional Fairness through Marginal Fairnesscited by 11
  30. 2021WordBias: An Interactive Visual Tool for Discovering Intersectional Biases Encoded in Word Embeddingscited by 8
  31. 2022Debiasing Word Embeddings with Nonlinear Geometrycited by 3
  32. 2022MANI-Rank: Multiple Attribute and Intersectional Group Fairness for Consensus Rankingcited by 2
  33. 2020Intersectional Affirmative Action Policies for Top-k Candidates Selectioncited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 5; 2024: 12; 2025: 21; 2026: 3.

41 papers.

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  1. 2023A Survey on Fairness in Large Language Modelscited by 91
  2. 2024The Pursuit of Fairness in Artificial Intelligence Models: A Surveycited by 13
  3. 2025Generalized Venn and Venn-Abers Calibration with Applications in Conformal Predictioncited by 6
  4. 2025PersonaTwin: A Multi-Tier Prompt Conditioning Framework for Generating and Evaluating Personalized Digital Twinscited by 5
  5. 2023Adaptation Speed Analysis for Fairness-aware Causal Modelscited by 4
  6. 2024Long-Term Fairness Inquiries and Pursuits in Machine Learning: A Survey of Notions, Methods, and Challengescited by 4
  7. 2025Who Evaluates AI's Social Impacts? Mapping Coverage and Gaps in First and Third Party Evaluationscited by 4
  8. 2024Different Horses for Different Courses: Comparing Bias Mitigation Algorithms in MLcited by 3
  9. 2025HInter: Exposing Hidden Intersectional Bias in Large Language Modelscited by 3
  10. 2025Measuring multi-calibrationcited by 3
  11. 2025Investigating Intersectional Bias in Large Language Models using Confidence Disparities in Coreference Resolutioncited by 3
  12. 2024Fairness Auditing with Multi-Agent Collaborationcited by 2
29 more
  1. 2024Runtime Monitoring and Enforcement of Conditional Fairness in Generative AIscited by 2
  2. 2024Measuring Model-Induced Discrimination via Efficient Fairness Approximationcited by 2
  3. 2024Fair Clustering for Data Summarization: Improved Approximation Algorithms and Complexity Insightscited by 2
  4. 2025Bias Detection via Maximum Subgroup Discrepancycited by 2
  5. 2025Representative Ranking for Deliberation in the Public Spherecited by 2
  6. 2025Critical Appraisal of Fairness Metrics in Clinical Predictive AIcited by 2
  7. 2025Machine Learning with Multitype Protected Attributes: Intersectional Fairness through Regularisationcited by 2
  8. 2023Fair Without Leveling Down: A New Intersectional Fairness Definitioncited by 1
  9. 2023Intersectionality and Testimonial Injustice in Medical Recordscited by 1
  10. 2023Detecting algorithmic bias in medical-AI models using treescited by 1
  11. 2024ProxiMix: Enhancing Fairness with Proximity Samples in Subgroupscited by 1
  12. 2025Bayes-Optimal Fair Classification with Multiple Sensitive Featurescited by 1
  13. 2025Intersectional Divergence: Measuring Fairness in Regressioncited by 1
  14. 2025Selecting for Less Discriminatory Algorithms: A Relational Search Framework for Navigating Fairness-Accuracy Trade-offs in Practicecited by 1
  15. 2025Size-adaptive Hypothesis Testing for Fairnesscited by 1
  16. 2025Towards Universal Debiasing for Language Models-based Tabular Data Generationcited by 1
  17. 2025Intersectional Fairness in Vision-Language Models for Medical Image Disease Classificationcited by 1
  18. 2024Equity in Healthcare: Analyzing Disparities in Machine Learning Predictions of Diabetic Patient Readmissionscited by 0
  19. 2024Fairpriori: Improving Biased Subgroup Discovery for Deep Neural Network Fairnesscited by 0
  20. 2024NLPGuard: A Framework for Mitigating the Use of Protected Attributes by NLP Classifierscited by 0
  21. 2024Fair Clustering with Minimum Representation Constraintscited by 0
  22. 2025Fairness-Aware Low-Rank Representation Fine-Tuningcited by 0
  23. 2025Algorithmic Fairness: Not a Purely Technical but Socio-Technical Propertycited by 0
  24. 2025Toward Substantive Intersectional Algorithmic Fairness: Desiderata for a Feminist Approachcited by 0
  25. 2025Auditability and the Landscape of Distance to Multicalibrationcited by 0
  26. 2025How Large Language Models Systematically Misrepresent American Climate Opinionscited by 0
  27. 2026Intersectional Fairness via Mixed-Integer Optimizationcited by 0
  28. 2026Generalizing Fair Top-k Selection: An Integrative Approachcited by 0
  29. 2026Rater State Bias in RLHF Preference Data: An Audit Frameworkcited by 0