Stability and discrimination trade-offs of fairness mitigation

Establish whether bias-mitigation steps, including reweighing and per-group threshold shifts, yield a stable passing fairness verdict without sacrificing model discrimination as measured by AUROC or AUPRC.

Background

Fairness audits convert continuous metrics into binary pass-or-fail decisions, but uncertainty in the metric does not automatically establish whether the resulting verdict will remain unchanged across repeated audits. Bias-mitigation procedures may improve a point-estimate fairness metric while producing verdicts that remain sensitive to cohort variation.

The unresolved issue is whether mitigation procedures can simultaneously secure a stable passing verdict and preserve predictive discrimination, rather than improving fairness only at the cost of AUROC or AUPRC. The paper evaluates reweighing and threshold shifting on the Texas-100X hospital length-of-stay dataset, but the broader trade-off remains an open issue beyond the reported cohort and experimental setting.