Le développement d'une IA explicable: entre principes éthiques généraux et mesures concrètes

AI engineers need applicable guidelines for implementing ethical principles into their technological solutions. But how can this be achieved? In this article, we take the development of Explainable Artificial Intelligence (XAI) as our starting point. First, we challenge the universalist approach, the view according to which some measures are necessary or sufficient for XAI in every context. Then, we propose a normative methodology for evaluating XAI measures that is adapted to specific contexts. This approach better integrates ethics into AI development by offering an adaptable and pragmatic method for engineers, regulators, ethical researchers, and decision-makers.