Legal Infrastructure for Transformative AI Governance
Gillian K. Hadfield

TL;DR
This paper emphasizes the importance of establishing legal and regulatory infrastructure, such as registration regimes and regulatory markets, to effectively govern transformative AI developments beyond just setting substantive rules.
Contribution
It proposes specific legal frameworks like registration regimes and regulatory markets to enhance AI governance infrastructure for transformative AI.
Findings
Registration regimes for frontier models can improve oversight.
Identification regimes for autonomous agents aid accountability.
Regulatory markets can foster private sector innovation in AI regulation.
Abstract
Most of our AI governance efforts focus on substance: what rules do we want in place? What limits or checks do we want to impose on AI development and deployment? But a key role for law is not only to establish substantive rules but also to establish legal and regulatory infrastructure to generate and implement rules. The transformative nature of AI calls especially for attention to building legal and regulatory frameworks. In this PNAS Perspective piece I review three examples I have proposed: the creation of registration regimes for frontier models; the creation of registration and identification regimes for autonomous agents; and the design of regulatory markets to facilitate a role for private companies to innovate and deliver AI regulatory services.
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Taxonomy
TopicsEthics and Social Impacts of AI · Artificial Intelligence in Law · Law, AI, and Intellectual Property
