Liability and Insurance for Catastrophic Losses: the Nuclear Power Precedent and Lessons for AI
This addresses the risk of catastrophic AI harms for society by drawing on the nuclear power precedent to propose a liability and insurance framework, which is an incremental application of existing legal concepts to a new domain.
The paper tackles the problem of catastrophic losses from autonomous AI systems by proposing that developers be assigned limited, strict, and exclusive liability for Critical AI Occurrences, with mandatory insurance to address judgment-proofness and leverage insurers' risk-management capabilities.
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.