前沿人工智能监管：管理新兴的公共安全风险

Frontier AI Regulation: Managing Emerging Risks to Public Safety

July 6, 2023

作者: Markus Anderljung, Joslyn Barnhart, Jade Leung, Anton Korinek, Cullen O'Keefe, Jess Whittlestone, Shahar Avin, Miles Brundage, Justin Bullock, Duncan Cass-Beggs, Ben Chang, Tantum Collins, Tim Fist, Gillian Hadfield, Alan Hayes, Lewis Ho, Sara Hooker, Eric Horvitz, Noam Kolt, Jonas Schuett, Yonadav Shavit, Divya Siddarth, Robert Trager, Kevin Wolf

cs.AI

摘要

先进的人工智能模型为人类带来巨大好处的同时也伴随着风险，社会需要积极管理这些风险。在本文中，我们关注所谓的“前沿人工智能”模型：高度功能强大的基础模型，可能具有足以对公共安全造成严重风险的危险能力。前沿人工智能模型带来了独特的监管挑战：危险能力可能出乎意料地出现；难以坚固地防止已部署的模型被滥用；以及难以阻止模型的能力广泛扩散。为了解决这些挑战，至少需要三个用于监管前沿模型的基本要素：（1）标准制定流程，以确定前沿人工智能开发者的适当要求；（2）注册和报告要求，为监管机构提供对前沿人工智能开发过程的可见性；以及（3）机制，以确保遵守前沿人工智能模型的开发和部署安全标准。行业自律是重要的第一步。然而，需要更广泛的社会讨论和政府干预来建立标准并确保遵守这些标准。我们考虑了几种实现这一目标的选择，包括授予监管机构执法权力和前沿人工智能模型的许可制度。最后，我们提出了一套初始的安全标准。这些标准包括进行部署前的风险评估；对模型行为进行外部审查；使用风险评估来指导部署决策；以及监测和回应有关模型能力和部署后使用的新信息。我们希望这一讨论有助于更广泛地探讨如何平衡公共安全风险和人工智能开发前沿的创新益处。

English

Advanced AI models hold the promise of tremendous benefits for humanity, but society needs to proactively manage the accompanying risks. In this paper, we focus on what we term "frontier AI" models: highly capable foundation models that could possess dangerous capabilities sufficient to pose severe risks to public safety. Frontier AI models pose a distinct regulatory challenge: dangerous capabilities can arise unexpectedly; it is difficult to robustly prevent a deployed model from being misused; and, it is difficult to stop a model's capabilities from proliferating broadly. To address these challenges, at least three building blocks for the regulation of frontier models are needed: (1) standard-setting processes to identify appropriate requirements for frontier AI developers, (2) registration and reporting requirements to provide regulators with visibility into frontier AI development processes, and (3) mechanisms to ensure compliance with safety standards for the development and deployment of frontier AI models. Industry self-regulation is an important first step. However, wider societal discussions and government intervention will be needed to create standards and to ensure compliance with them. We consider several options to this end, including granting enforcement powers to supervisory authorities and licensure regimes for frontier AI models. Finally, we propose an initial set of safety standards. These include conducting pre-deployment risk assessments; external scrutiny of model behavior; using risk assessments to inform deployment decisions; and monitoring and responding to new information about model capabilities and uses post-deployment. We hope this discussion contributes to the broader conversation on how to balance public safety risks and innovation benefits from advances at the frontier of AI development.