高风险AI全球监管比较：FAIR原则与合规工件
原标题：Global AI Regulations for FAIR and Ethics in High-Risk Use Cases: A Comparative Review
AI 摘要
本文对欧盟、美国和中国的高风险AI监管框架进行了比较分析，构建了涵盖风险分类、义务、执行和FAIR原则的评估矩阵，并针对脑电图康复机器人、CBDC债务催收和GPU资源分配三个用例进行压力测试。研究发现跨司法管辖区存在互操作性弱、义务操作化困难及关键基础设施治理不足等缺口，并提出了基于RDF/OWL、SHACL和PROV-O的机器可检查合规工件模式“Knowledge Blocks”以支持合规设计。
正文节选
Global AI Regulations for FAIR and Ethics in High-Risk Use Cases: A Comparative Review Abstract AI governance is shifting from voluntary ethics to enforceable, risk-based regulation, yet cross-jurisdictional divergence creates compliance uncertainty for operators of high-stakes AI. We present a comparative matrix for the EU, US, and China that maps (i) risk classification triggers, (ii) binding obligations, (iii) enforcement and accountability mechanisms, and (iv) the degree to which FAIR princi