Still Malignant if You Were a Woman? Auditing Group and Counterfactual Fairness in Dermatological AI

This research addresses algorithmic fairness in medical AI, specifically focusing on dermatological diagnosis systems. We audit both group fairness and counterfactual fairness to ensure that AI-driven skin lesion classification systems provide equitable diagnostic accuracy across different demographic groups, particularly examining gender-based disparities in malignancy detection.