Explainability and justification of automatic-decision making: A conceptual framework and a practical application

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Authors: Sarra Tajouri, Yves Meinard, Alexis Tsoukiàs, Thierry Kirat
Cited by: 0
References: 4

Abstract

Explainability of algorithmic decision-making systems is both a regulatory objective and an area of intense research. The article argues that a crucial condition for the acceptability of algorithmic decision-making systems is that decisions must be justified in the eyes of their recipients. We make a clear distinction between explanation and justification. Explanations describe how a decision was made, while justifications give reasons that aim to make the decision acceptable. We propose a conceptual framework of explanations and justifications, based on Habermas's theory of communicative action and Perelman's New Rhetoric theory of law. This framework helps to analyze how different forms of explanation can support or fail to support justification. We illustrate our approach with a case study on university admissions in France.

Fields of Study & Subjects

Explainable Artificial Intelligence (XAI) Ethics and Social Impacts of AI Digitalization Law and Regulation

Publication details

Journal / source
HAL
Pages
31 pages
Publication date
2 March 2026
Language
EN
Document type
Preprint