AI Governance through Markets

TL;DR

This paper advocates for integrating market-based mechanisms like insurance and auditing into AI governance to complement regulation, aiming to incentivize responsible AI development and address risk management.

Contribution

It introduces four emerging market governance vectors—insurance, auditing, procurement, and due diligence—and discusses their potential to improve AI risk management.

Findings

Market mechanisms can align AI risk with financial incentives.

Standardized AI disclosures can promote responsible development.

Market-based approaches complement traditional regulation.

Abstract

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.