mlsanityData to 14 Oct 2026

A Causal Bayesian Networks Viewpoint on Fairness

arXiv 1907.06430 ↗First posted 15 Jul 2019stat.ML cs.LGcited by 19

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Abstract (arXiv)

We offer a graphical interpretation of unfairness in a dataset as the presence of an unfair causal path in the causal Bayesian network representing the data-generation mechanism. We use this viewpoint to revisit the recent debate surrounding the COMPAS pretrial risk assessment tool and, more generally, to point out that fairness evaluation on a model requires careful considerations on the patterns of unfairness underlying the training data. We show that causal Bayesian networks provide us with a powerful tool to measure unfairness in a dataset and to design fair models in complex unfairness scenarios.

Key facts. Cited by 19 papers in the map (data through 14 Oct 2026). First posted on arXiv 15 Jul 2019.

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Citing papers per year: 2021: 2; 2022: 10; 2023: 1; 2024: 2; 2025: 2; 2026: 2.

19 papers.

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  1. 2022Bias Mitigation for Machine Learning Classifiers: A Comprehensive Surveycited by 125
  2. 2022Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluationcited by 59
  3. 2022Fairness in Recommendation: Foundations, Methods and Applicationscited by 27
  4. 2025Virtual Agent Economiescited by 21
  5. 2022What-is and How-to for Fairness in Machine Learning: A Survey, Reflection, and Perspectivecited by 18
  6. 2022D-BIAS: A Causality-Based Human-in-the-Loop System for Tackling Algorithmic Biascited by 18
  7. 2022Selection, Ignorability and Challenges With Causal Fairnesscited by 16
  8. 2023A Review of the Role of Causality in Developing Trustworthy AI Systemscited by 14
  9. 2022The Long Arc of Fairness: Formalisations and Ethical Discoursecited by 13
  10. 2021Learning to be Fair: A Consequentialist Approach to Equitable Decision-Makingcited by 11
  11. 2022Why Fair Labels Can Yield Unfair Predictions: Graphical Conditions for Introduced Unfairnesscited by 10
  12. 2022Bias and unfairness in machine learning models: a systematic literature reviewcited by 7
7 more
  1. 2022What Is Fairness? On the Role of Protected Attributes and Fictitious Worldscited by 6
  2. 2025Counterfactually Fair Reinforcement Learning via Sequential Data Preprocessingcited by 5
  3. 2024Long-Term Fairness Inquiries and Pursuits in Machine Learning: A Survey of Notions, Methods, and Challengescited by 4
  4. 2024Learning Fairer Representations with FairVICcited by 2
  5. 2021A Causal Approach for Unfair Edge Prioritization and Discrimination Removalcited by 1
  6. 2026Towards Provably Fair Machine Learning: Bayesian Approaches For Consistent and Transparent Predictionscited by 0
  7. 2026The Role of Uncertainty in Assessing the Fairness of Machine Learning Modelscited by 0