There is an urgent need to identify both short and long-term risks from newly emerging types of Artificial Intelligence (AI), as well as available risk management measures. In response, and to support global efforts in regulating AI and writing safety standards, we compile an extensive catalog of risk sources and risk management measures for general-purpose AI (GPAI) systems, complete with descriptions and supporting examples where relevant. This work involves identifying technical, operational, and societal risks across model development, training, and deployment stages, as well as surveying established and experimental methods for managing these risks. To the best of our knowledge, this paper is the first of its kind to provide extensive documentation of both GPAI risk sources and risk management measures that are descriptive, self-contained and neutral with respect to any existing regulatory framework. This work intends to help AI providers, standards experts, researchers, policymakers, and regulators in identifying and mitigating systemic risks from GPAI systems. For this reason, the catalog is released under a public domain license for ease of direct use by stakeholders in AI governance and standards.

翻译：随着新型人工智能（AI）技术的不断涌现，亟需识别其带来的短期与长期风险，并明确可用的风险管理措施。为此，并为了支持全球范围内的人工智能监管与安全标准制定工作，我们编纂了一份涵盖通用人工智能（GPAI）系统风险来源与风险管理措施的详尽目录，其中包含相关描述及适当的示例支持。这项工作涉及识别模型开发、训练与部署阶段的技术性、操作性与社会性风险，同时系统梳理了管理这些风险的成熟方法与实验性手段。据我们所知，本文首次以描述性、自包含且独立于任何现有监管框架的立场，对GPAI风险来源与风险管理措施进行了广泛记录。本工作旨在帮助AI提供方、标准专家、研究人员、政策制定者及监管机构识别并缓解GPAI系统带来的系统性风险。为此，该目录以公共领域许可协议发布，以便人工智能治理与标准制定相关方直接使用。