[en] 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 nonconservative 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
Disciplines :
Sciences informatiques
Auteur, co-auteur :
Poe, Robert Lee ; Laboratorio Interdisciplinare Diritti e Regole (LIDER-Lab), Sant'Anna School of Advanced Studies, Italy
EL MESTARI, Soumia Zohra ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > IRiSC
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
The Conflict Between Algorithmic Fairness and Non-Discrimination: An Analysis of Fair Automated Hiring
Date de publication/diffusion :
03 juin 2024
Nom de la manifestation :
The 2024 ACM Conference on Fairness, Accountability, and Transparency
Organisateur de la manifestation :
Association for Computing Machinery,New York NY, United States
Lieu de la manifestation :
Rio de Janeiro, Brésil
Date de la manifestation :
3rd June-6th June 2024
Manifestation à portée :
International
Titre du périodique :
Journal of the Association for Computing Machinery
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