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.

翻译：先进人工智能模型有望为人类带来巨大福祉，但社会需主动管控伴随的风险。本文聚焦于我们称之为"前沿人工智能"的模型：即具备潜在危险能力、可能对公共安全构成严重威胁的高度能力基础模型。前沿人工智能模型构成独特的监管挑战：危险能力可能意外涌现；难以有效防止已部署模型被滥用；且模型能力的广泛扩散难以遏制。应对这些挑战至少需要构建前沿模型监管的三大基石：（1）制定标准流程以明确对前沿人工智能开发者的合理要求；（2）建立注册与报告机制，使监管机构能够了解前沿人工智能开发流程；（3）建立确保前沿人工智能模型开发与部署合规安全标准的机制。行业自律是重要起点，但制定标准并确保合规仍需更广泛的社会讨论与政府干预。为此我们考虑多种方案，包括赋予监管机构执法权及对前沿人工智能模型实施许可制度。最后提出初步安全标准：开展部署前风险评估；实施模型行为外部审查；以风险评估指导部署决策；监测并响应部署后模型能力与使用的新信息。期待本讨论能促进关于如何平衡人工智能前沿发展带来的公共安全风险与创新收益的更广泛思考。