arxivcs.LGcs.AIcs.CRcs.CY2026-07-18
Privacy Cost as Equity Input: A Group Fairness Criterion for Differentially Private Machine Learning
Differential privacy (DP) is increasingly deployed to limit membership inference risk in machine-learning systems. Prior work has shown that DP-SGD can widen accuracy disparities across demographic groups, but this framing treats fairness as a purely outcome-side concern. We argu…