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A Geometric Theory of Robust Fairness Audits
Neighborhood-based fairness audits evaluate individual fairness by comparing predictions among similar individuals in feature space. Despite their widespread use, little is known about the robustness of the auditing procedure itself. Because these audits rely on nearest neighbor relationships, small perturbations in feature space can alter local neighborhoods and produce different fairness assessments even when model predictions remain unchanged. We develop a geometric framework for analyzing the robustness of neighborhood-based fairness audits under bounded perturbations. Our analysis establi
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-25T16:58:57.000Z
First collected: 2026-09-21T09:42:05.193Z. This is not the publication date.