Fairness Is Not Enough: Auditing Competence and Intersectional Bias in AI-powered Resume Screening

תקציר מקורי באנגליתarXiv:2507.11548v3 Announce Type: replace-cross Abstract: The use of publicly available generative AI systems for resume evaluation is often justified by the assumption that these tools reduce bias relative to human judgment. However, this framing leaves a prior question unresolved: whether these systems are capable of performing the evaluative task at all. This study presents a two-part audit of eight widely used AI platforms used for resume screening. Drawing on the concept of the Illusion of Neutrality, the study examines cases in which systems appear demographically unbiased because they lack the ability to meaningfully differentiate among candidates. Experiment 1 evaluates racial and gender bias using matched fictitious resumes and finds that bias persists in context-dependent and int