论文标题
高导力AI风险管理的可行指南：针对AI灾难性风险的标准
Actionable Guidance for High-Consequence AI Risk Management: Towards Standards Addressing AI Catastrophic Risks
论文作者
论文摘要
人工智能（AI）系统可以提供许多有益的功能，也可以提供不良事件的风险。一些AI系统可能会出现在社会规模上具有很高或灾难性后果的事件的风险。美国国家标准技术研究所（NIST）一直在开发NIST人工智能风险管理框架（AI RMF），作为对AI开发人员和其他人的AI风险评估和管理的自愿指导。 NIST为了解决带有灾难性后果的事件的风险，表示有必要将高级原则转化为可行的风险管理指导。 在本文档中，我们提供了详细的可操作指示建议，旨在识别和管理具有很高或灾难性后果的事件的风险，目的是作为AI RMF版本1.0的NIST的风险管理实践资源（2023年1月于2023年发行），或者针对AI RMF用户或其他AI风险管理用户和其他AI风险管理管理人员的资源。我们还为建议提供方法。 我们为AI RMF 1.0提供了可行的指导建议：识别AI系统潜在的意外用途和滥用的风险；在风险评估和影响评估范围内包括灾难性风险因素；识别和减轻人权危害；并报告有关AI风险因素在内的信息，包括灾难性风险因素。 此外，我们还为AI RMF或补充出版物的以后版本的路线图提供有关其他问题的建议。其中包括：提供AI RMF概况，并具有越来越多的多功能或通用AI的辅助指南。 我们的目标是使这项工作成为具体的风险管理实践的贡献，并激发有关如何解决AI标准中灾难性风险和相关问题的建设性对话。
Artificial intelligence (AI) systems can provide many beneficial capabilities but also risks of adverse events. Some AI systems could present risks of events with very high or catastrophic consequences at societal scale. The US National Institute of Standards and Technology (NIST) has been developing the NIST Artificial Intelligence Risk Management Framework (AI RMF) as voluntary guidance on AI risk assessment and management for AI developers and others. For addressing risks of events with catastrophic consequences, NIST indicated a need to translate from high level principles to actionable risk management guidance. In this document, we provide detailed actionable-guidance recommendations focused on identifying and managing risks of events with very high or catastrophic consequences, intended as a risk management practices resource for NIST for AI RMF version 1.0 (released in January 2023), or for AI RMF users, or for other AI risk management guidance and standards as appropriate. We also provide our methodology for our recommendations. We provide actionable-guidance recommendations for AI RMF 1.0 on: identifying risks from potential unintended uses and misuses of AI systems; including catastrophic-risk factors within the scope of risk assessments and impact assessments; identifying and mitigating human rights harms; and reporting information on AI risk factors including catastrophic-risk factors. In addition, we provide recommendations on additional issues for a roadmap for later versions of the AI RMF or supplementary publications. These include: providing an AI RMF Profile with supplementary guidance for cutting-edge increasingly multi-purpose or general-purpose AI. We aim for this work to be a concrete risk-management practices contribution, and to stimulate constructive dialogue on how to address catastrophic risks and associated issues in AI standards.
