arXiv Machine Learning
Jul 9

A Distributionally Robust Optimisation Approach to Fair Credit Scoring

arXiv:2402. 01811v2 Announce Type: replace Abstract: Credit scoring has been catalogued by the European Commission and the Executive Office of the US President as a high-risk classification task, in light of the potential harms of making loan approval decisions based on models that would be biased against certain groups.

By Pablo Casas, Huan Yu, Christophe Mues
arXiv AI
Aug 28

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

The paper introduces REMI, a framework that treats counterfactual fairness as a relational invariant discovery problem. By learning over paired examples, REMI identifies input regions where fairness is violated and generates interpretable rule-based models—fairness invariants—that can block or relabel unfair predictions without retraining the underlying model. Experiments on symbolic and neural network programs show REMI localizes fairness bugs in over 83% of cases and reduces discriminatory decisions in black-box models by up to 70%.

By Ranit Debnath Akash, Ashish Kumar, Gang Tan, Saeid Tizpaz-Niari