Regulatory Markets: The Future of AI Governance
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Abstract (arXiv)
Appropriately regulating artificial intelligence is an increasingly urgent and widespread policy challenge. We identify two primary, competing problem. First is a technical deficit: Legislatures and regulatory face significant challenges in rapidly translating conventional command-and-control legal requirements into technical requirements. Second is a democratic deficit: Over-reliance on industry to provide technical standards fails to ensure that the many values-based decisions that must be made to shape AI development and deployment are made by democratically accountable public, not private, actors. We propose a solution: regulatory markets, in which governments require the targets of regulation to purchase regulatory services from a government-licensed private regulator. This approach to AI regulation could overcome the limitations of both command-and-control regulation and excessive delegation to industry. Regulatory markets could enable governments to establish policy priorities for the regulation of AI while relying on market forces and industry R&D efforts to pioneer the technical methods of regulation that best achieve policymakers' stated objectives.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 0 of its 3 references that are in the map. First posted on arXiv 11 Apr 2023.
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