#fairness-testing News & Analysis

Perturbation Effects on Accuracy and Fairness among Similar Individuals

Researchers introduce Robust Individual Fairness (RIF), a new evaluation framework that exposes how adversarial perturbations simultaneously compromise both prediction accuracy and fairness in neural networks. The proposed RIFair tool reveals hidden vulnerabilities that traditional robustness-only or fairness-only testing overlooks across multiple datasets and architectures.