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Causal Reasoning for Algorithmic Fairness

arXiv 1805.05859 ↗First posted 15 May 2018cs.AI cs.CYcited by 51

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Abstract (arXiv)

In this work, we argue for the importance of causal reasoning in creating fair algorithms for decision making. We give a review of existing approaches to fairness, describe work in causality necessary for the understanding of causal approaches, argue why causality is necessary for any approach that wishes to be fair, and give a detailed analysis of the many recent approaches to causality-based fairness.

Key facts. Cited by 51 papers in the map (data through 14 Oct 2026). First posted on arXiv 15 May 2018.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 9; 2022: 16; 2023: 9; 2024: 8; 2025: 6; 2026: 3.

51 papers.

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  1. 2023CLadder: Assessing Causal Reasoning in Language Modelscited by 107
  2. 2021Bias in Machine Learning Software: Why? How? What to do?cited by 93
  3. 2021Socially Responsible AI Algorithms: Issues, Purposes, and Challengescited by 56
  4. 2022Causal Conceptions of Fairness and their Consequencescited by 38
  5. 2021Strategic Instrumental Variable Regression: Recovering Causal Relationships From Strategic Responsescited by 32
  6. 2022Causal Explanations and XAIcited by 30
  7. 2022FaiRR: Faithful and Robust Deductive Reasoning over Natural Languagecited by 29
  8. 2021When Fair Ranking Meets Uncertain Inferencecited by 22
  9. 2021Fairness On The Ground: Applying Algorithmic Fairness Approaches to Production Systemscited by 21
  10. 2022Challenges in Applying Explainability Methods to Improve the Fairness of NLP Modelscited by 20
  11. 2023Causal Deep Learningcited by 20
  12. 2024Auditing the Use of Language Models to Guide Hiring Decisionscited by 20
38 more
  1. 2022What-is and How-to for Fairness in Machine Learning: A Survey, Reflection, and Perspectivecited by 18
  2. 2022Selection, Ignorability and Challenges With Causal Fairnesscited by 16
  3. 2024The Pursuit of Fairness in Artificial Intelligence Models: A Surveycited by 13
  4. 2021FairCanary: Rapid Continuous Explainable Fairnesscited by 12
  5. 2022Simplicity Bias Leads to Amplified Performance Disparitiescited by 11
  6. 2024How to be fair? A study of label and selection biascited by 11
  7. 2022Why Fair Labels Can Yield Unfair Predictions: Graphical Conditions for Introduced Unfairnesscited by 10
  8. 2022Learning Counterfactually Invariant Predictorscited by 10
  9. 2023Causal Fairness under Unobserved Confounding: A Neural Sensitivity Frameworkcited by 10
  10. 2023Fairness Aware Counterfactuals for Subgroupscited by 9
  11. 2022Multi-disciplinary fairness considerations in machine learning for clinical trialscited by 8
  12. 2022Subverting Fair Image Search with Generative Adversarial Perturbationscited by 5
  13. 2024What is Fair? Defining Fairness in Machine Learning for Healthcited by 5
  14. 2025Overcoming Fairness Trade-offs via Pre-processing: A Causal Perspectivecited by 5
  15. 2021Causal Inference in medicine and in health policy, a summarycited by 4
  16. 2024Counterfactual Fairness Is Not Demographic Parity, and Other Observationscited by 4
  17. 2024Addressing Both Statistical and Causal Gender Fairness in NLP Modelscited by 4
  18. 2022Causal Fairness Assessment of Treatment Allocation with Electronic Health Recordscited by 3
  19. 2023Causal Dependence Plotscited by 3
  20. 2023Causal Discovery Under Local Privacycited by 3
  21. 2023Procedural Fairness Through Decoupling Objectionable Data Generating Componentscited by 3
  22. 2024A New Paradigm for Counterfactual Reasoning in Fairness and Recoursecited by 3
  23. 2024A Review of Fairness and A Practical Guide to Selecting Context-Appropriate Fairness Metrics in Machine Learningcited by 3
  24. 2025Counterfactual Fairness Evaluation of Machine Learning Models on Educational Datasetscited by 3
  25. 2025Uncovering Bias Paths with LLM-guided Causal Discovery: An Active Learning and Dynamic Scoring Approachcited by 3
  26. 2021Beyond traditional assumptions in fair machine learningcited by 2
  27. 2022SCALES: From Fairness Principles to Constrained Decision-Makingcited by 2
  28. 2023Designing Equitable Algorithmscited by 2
  29. 2025Causality Is Key to Understand and Balance Multiple Goals in Trustworthy ML and Foundation Modelscited by 2
  30. 2021Fairness Through Counterfactual Utilitiescited by 1
  31. 2022Identifiability of Causal-based Fairness Notions: A State of the Artcited by 1
  32. 2023An Information-Flow Perspective on Algorithmic Fairnesscited by 1
  33. 2025Modeling Fairness in Recruitment AI via Information Flowcited by 1
  34. 2026Trustworthy AI Suffers from Invariance Conflicts and Causality is The Solutioncited by 1
  35. 2022On the Need and Applicability of Causality for Fairness: A Unified Framework for AI Auditing and Legal Analysiscited by 0
  36. 2022Causal foundations of bias, disparity and fairnesscited by 0
  37. 2025Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinantscited by 0
  38. 2026Fairness risk and its privacy-enabled solution in AI-driven robotic applicationscited by 0

50 most cited of 51 All 51 (JSON)