Path-Specific Counterfactual Fairness

2018/02/22 by Silvia Chiappa, Chiappa, Silvia, Thomas P. S. Gillam +1 · 1 voice · 21 citations
Mathematics · #FOS: Computer and information sciences #Machine Learning (stat.ML) #stat.ML

paper · pdf · doi:10.48550/arxiv.1802.08139

arxiv created 2018/02/22 · arxiv published 2018/02/22 · arxiv updated 2018/02/23

Abstract

We consider the problem of learning fair decision systems in complex scenarios in which a sensitive attribute might affect the decision along both fair and unfair pathways. We introduce a causal approach to disregard effects along unfair pathways that simplifies and generalizes previous literature. Our method corrects observations adversely affected by the sensitive attribute, and uses these to form a decision. This avoids disregarding fair information, and does not require an often intractable computation of the path-specific effect. We leverage recent developments in deep learning and approximate inference to achieve a solution that is widely applicable to complex, non-linear scenarios.

Cited by

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• Algorithmic Fairness in AI Surrogates for End-of-Life Decision-Making
• Evidence Without Injustice: A New Counterfactual Test for Fair Algorithms
• Counterfactually Fair Conformal Prediction
• Partial Identification Approach to Counterfactual Fairness Assessment
• Calibrated Counterfactual Conformal Fairness (C³F): Post-hoc, Shift-Aware Coverage Parity via Conformal Prediction and Counterfactual Regularization
• Causal Fuzzing for Verifying Machine Unlearning
• CausalPre: Scalable and Effective Data Pre-Processing for Causal Fairness
• Fairness-Aware and Interpretable Policy Learning
• Algorithmic Fairness amid Social Determinants: Reflection, Characterization, and Approach
• FairDiffuseVQVAE: Sampling-Time Fairness in Tabular Diffusion via Conditional Refinement of Vector-Quantized Latents
• FairCauseSyn: Towards Causally Fair LLM-Augmented Synthetic Data Generation
• Path-specific effects for pulse-oximetry guided decisions in critical care
• DISCO: Mitigating Bias in Deep Learning with Conditional Distance Correlation
• FairPFN: A Tabular Foundation Model for Causal Fairness
• Uncovering Bias Paths with LLM-guided Causal Discovery: An Active Learning and Dynamic Scoring Approach
• Causally Fair Node Classification on Non-IID Graph Data
• Beyond One-Size-Fits-All: Inversion Learning for Highly Effective NLG Evaluation Prompts
• A Design Framework for operationalizing Trustworthy Artificial Intelligence in Healthcare: Requirements, Tradeoffs and Challenges for its Clinical Adoption
• GoT-CD: Graph-of-Thoughts Causal Discovery and the Fragility of Post-hoc Path-Specific Fairness Audits
• A conceptual synthesis of causal assumptions for causal discovery and inference

Discussions

• Path-Specific Counterfactual Fairness [pdf] [hn, 2 points, 0 comments]

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