Responsible AI: Binaries that Bind - Raso, Jennifer (McGill Law Journal / Revue de droit de McGill)

(untitled) (McGill Law Journal / Revue de droit de McGill, 2024)
This article examines responsible AI as a public law-like movement that seeks to (self)regulate the design and use of AI systems. Using socio-legal methods, and the Montréal Declaration for a Responsible Development of Artificial Intelligence as an illustrate example, it explores responsible AI’s upshots for digital government. Responsible AI initiatives, this article argues, rely on two binary distinctions: (1) between artificial and natural intelligence, and (2) between the future and present/past effects of AI systems. These conceptual binaries “bind” such initiatives to an impoverished understanding of what AI systems are, how they operate, and how they might be governed. To realize justice and fairness, especially in digital government, responsible AI projects must reconceive of AI systems and their regulation infrastructurally and agonistically.