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AI-based automated hiring systems cover a wide range of tools of varying complexity, from resume parsing tools to candidate selection models. Their close interference in economic and social life faces raising demands and investigations aiming to reduce the potential discrimination they may cause. This article covers the intersection of EU non-discrimination law and algorithmic fairness in the context of automated hiring systems. The paper analyzes the balance between equality of opportunity (formal and substantive) and equality of outcome, critiques the focus on non-conservative group fairness in machine learning, and discusses the legal implications of automated hiring systems under EU law. Additionally, it highlights often committed fallacies in relation to the process of de-biasing and advocates for a broader understanding of fairness in machine learning that aligns with EU legal standards and societal values.
Poe et al. (Mon,) studied this question.