AI Governance through Markets
It proposes a new approach to AI governance for regulators and researchers, but it is incremental as it builds on existing regulatory frameworks.
The paper argues that market governance mechanisms, such as insurance and auditing, should be used alongside regulation to incentivize responsible AI development by linking AI risk to financial risk and addressing capital allocation inefficiencies.
This paper argues that market governance mechanisms should be considered a key approach in the governance of artificial intelligence (AI), alongside traditional regulatory frameworks. While current governance approaches have predominantly focused on regulation, we contend that market-based mechanisms offer effective incentives for responsible AI development. We examine four emerging vectors of market governance: insurance, auditing, procurement, and due diligence, demonstrating how these mechanisms can affirm the relationship between AI risk and financial risk while addressing capital allocation inefficiencies. While we do not claim that market forces alone can adequately protect societal interests, we maintain that standardised AI disclosures and market mechanisms can create powerful incentives for safe and responsible AI development. This paper urges regulators, economists, and machine learning researchers to investigate and implement market-based approaches to AI governance.