映射美国联邦AI治理与部门脆弱性

中文摘要 AI 辅助

人工智能（AI）在不同部门构成不同级别的风险，但这些差异是否反映在美国联邦AI治理中？为帮助回答此问题，我们评估了684份联邦AI治理文件对14个部门和24种AI风险的覆盖情况。我们将覆盖度衡量为广度（即风险或部门在文件中被提及的频率）和深度（即风险或部门被讨论的实质性程度）。然后，我们将每种风险的部门覆盖模式与一项涉及272位专家的德尔菲研究的脆弱性评估进行比较。我们的分析发现覆盖存在显著差异：与鲁棒性、系统安全和治理相关的AI风险比社会经济、环境和新兴风险（包括多智能体风险）获得更多关注。公共行政、国家安全、信息和科学服务相对于其他部门（如金融和医疗保健）获得较高的覆盖水平，而专家认为这些部门对AI风险高度脆弱。通过映射当前覆盖并识别其与专家脆弱性评估的差异，我们揭示了潜在的AI治理缺口，这可能有助于为政府和行业的AI风险相关决策提供信息。

英文摘要

Artificial intelligence (AI) poses different levels of risk across sectors, but are these differences reflected in U.S. federal AI governance? To help answer this question, we assess 684 federal AI governance documents for their coverage of 14 sectors and 24 AI risks. We measure coverage as breadth (i.e., how frequently the risk or sector is addressed across documents) and depth (i.e., how substantively the risk or sector is discussed). We then compare sector coverage patterns for each of the 24 risks with vulnerability assessments from a Delphi study of 272 experts. Our analysis finds substantial variation in coverage: AI risks related to robustness, system security, and governance receive more attention than socioeconomic, environmental, and emerging risks, including multi-agent risks. Public administration, national security, information, and scientific services receive comparatively high levels of coverage relative to other sectors, such as finance and healthcare, which experts rate as highly vulnerable to AI risks. By mapping current coverage and identifying where it differs from expert assessments of vulnerability, we surface potential AI governance gaps which may help inform AI risk-related decisions across government and industry.

发表机构

• MARS
• MIT FutureTech（麻省理工学院未来科技）
• Cambridge Boston Alignment Initiative（剑桥-波士顿对齐倡议）

机构由 AI 辅助整理，请以论文原文为准。