Liability and Insurance for Catastrophic Losses: the Nuclear Power Precedent and Lessons for AI

TL;DR

This paper advocates for strict liability and mandatory insurance for AI developers, drawing lessons from nuclear power, to better manage catastrophic AI risks and facilitate regulation.

Contribution

It introduces a liability framework for AI based on nuclear precedents, emphasizing mandatory insurance and insurer roles in risk mitigation.

Findings

Liability and insurance can improve risk management for AI catastrophes.

Insurers can play a regulatory role through risk modeling and monitoring.

The nuclear precedent offers valuable lessons for AI risk governance.

Abstract

As AI systems become more autonomous and capable, experts warn of them potentially causing catastrophic losses. Drawing on the successful precedent set by the nuclear power industry, this paper argues that developers of frontier AI models should be assigned limited, strict, and exclusive third party liability for harms resulting from Critical AI Occurrences (CAIOs) - events that cause or easily could have caused catastrophic losses. Mandatory insurance for CAIO liability is recommended to overcome developers' judgment-proofness, mitigate winner's curse dynamics, and leverage insurers' quasi-regulatory abilities. Based on theoretical arguments and observations from the analogous nuclear power context, insurers are expected to engage in a mix of causal risk-modeling, monitoring, lobbying for stricter regulation, and providing loss prevention guidance in the context of insuring against heavy-tail risks from AI. While not a substitute for regulation, clear liability assignment and mandatory insurance can help efficiently allocate resources to risk-modeling and safe design, facilitating future regulatory efforts.