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Peer-Reviewed Publication
Lancet Digit Health2026;8(6):101005.June 1, 2026Journal Article

Impracticality of banning collection of data on race and ethnicity in artificial intelligence-enabled health care in France.

Benjamin C Guinhouya1, Thomas Morgenroth2, Fabio Boudis3, Geoffroy K Apété4, Gloria T Dossou5, Gilles Gasso6, Djamel Zitouni7
1University of Lille, Inserm, CHU Lille, U1366, Cancer Research Center of Lille (CRC Lille), F-59000 Lille, France; UFR 3S - ILIS, University of Lille, F-59000 Lille, France. Electronic address: benjamin.guinhouya@univ-lille.fr.
2University of Strasbourg, Faculty of Pharmacy, CEIE EA 7307, CNRS FR 3241, F-67401 Illkirch-Graffenstaden, France.
3UFR 3S - ILIS, University of Lille, F-59000 Lille, France; Department of Medical Information, CHU Lille, F-59000 Lille, France.
4UFR 3S - ILIS, University of Lille, F-59000 Lille, France.
5UFR 3S - ILIS, University of Lille, F-59000 Lille, France; University of Lille, ULR 4999 LUMEN, F-59000 Lille, France.
6University of Normandie, INSA Rouen Normandie, UNIROUEN, UNIHAVRE, Laboratoire d'Informatique, du Traitement de l'Information et des Systèmes (LITIS), F-76000 Rouen, France.
7University of Lille, Inserm, CHU Lille, U1366, Cancer Research Center of Lille (CRC Lille), F-59000 Lille, France; UFR 3S - Pharmacy, University of Lille, F-59000 Lille, France.
PubMed DOI

Abstract

Artificial intelligence (AI) or machine learning (ML) are revolutionising health care, enhancing diagnostics and treatment through AI-enabled medical devices. However, the effectiveness of AI or ML models is hindered by substantial biases, particularly against minority populations such as African and Afro-descendant people. In this Viewpoint, we discuss the colour-blind policy of France, which pro…

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