Responsible AI

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.

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Publication Details

Journal
McGill Law Journal
Published
2024-10-01
DOI
https://doi.org/10.26443/law.v69i4.1627
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
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Responsible AI

Jennifer Raso
McGill Law Journal
Ethics and Social Impacts of AI
article

Responsible AI

Jennifer Raso
article en

Abstract

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.

McGill Law JournalVol. 69(4)
McGill University (CA)
Openalex Percentile: Top 66%
Ethics and Social Impacts of AI
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