Also known as: AI Accountability · Artificial Intelligence Accountability
La responsabilité en IA est l’attribution et l’application de la responsabilité pour le développement, le déploiement, l’exploitation et les effets des systèmes d’IA. Elle repose sur des pratiques de gouvernance telles que la transparence, l’assurance, la documentation, l’évaluation et les mécanismes qui rendent les parties responsables comptables des risques ou des dommages.
AI accountability is the process, heavily reliant on transparency and assurance practices, of holding entities answerable for the risks and/or harms of the AI systems they develop or deploy. This is closest to the definition adopted by the Trade and Technology Council (TTC) joint U.S.-EU set of AI terms, which defines accountability as an 'allocated responsibility' for system performance or for governance functions. Whereas OECD interpretive guidance distinguishes 'accountability' from 'responsibility' and 'liability,' the TTC definition embraces responsibility as part of accountability and includes a broader scope of governance activities. Accountability may require enforceable consequences. Such consequences, usually determined by regulators, courts, and the market, are accountability outputs. This Report focuses on developing and shaping 'accountability inputs,' which feed into systems of accountability.