Deep learning and other black-box models are becoming more and more popular today. Despite their high performance, they may not be accepted ethically or legally because of their lack of explainability. This paper presents the increasing number of legal requirements on machine learning model interpretability and explainability in the context of private and public decision making. It then explains how those legal requirements can be implemented into machine-learning models and concludes with a call for more inter-disciplinary research on explainability.

langue originaleAnglais
Pages (de - à)149-169
Nombre de pages21
journalArtificial Intelligence & Law
Numéro de publication2
Les DOIs
Etat de la publicationPublié - juin 2021

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