灾难性损失的责任与保险:核电先例及对人工智能的启示

Cristian Trout
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引用次数: 0

摘要

随着人工智能系统的自主性和能力越来越强,专家们警告说它们可能会造成灾难性的损失。借鉴核电行业的成功先例,本文认为,对于关键人工智能事件(CAIOs)--造成或很可能造成灾难性损失的事件--所造成的损害,应由前沿人工智能模型的开发者承担有限、严格和排他性的第三方责任。建议对 CAIO 责任进行强制保险,以克服开发者的判断能力,缓解赢家诅咒动态,并利用保险公司的准监管能力。根据理论论证和类似核电背景下的观察,在人工智能重尾风险保险方面,保险公司应参与因果风险建模、监控、游说更严格的监管以及提供损失预防指导等一系列工作。虽然不能替代监管,但明确的责任分配和强制保险有助于将资源有效地分配给风险建模和安全设计,促进未来的监管工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Liability and Insurance for Catastrophic Losses: the Nuclear Power Precedent and Lessons for AI
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.
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