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Fairness Invariants: A Relational Approach to Explaining and Mitigating Fairness Bugs

arXiv · AI, language, vision and robotics · article · Aug 26, 2026 · UTC

Data-driven software systems are increasingly deployed in high-stakes socio-economic domains, from criminal justice to financial lending. However, these systems often exhibit individual discrimination---unjustified disparities in which a program yields different outcomes for similar individuals who differ only in their protected attributes (e.g., race, gender, age). While existing research has focused on detecting and quantifying these bugs, there remains a critical lack of principled mechanisms to explain and localize individual fairness bugs. Current explanation techniques are largely design

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