梳理AI风险评估与管理方法，助力合规可靠系统落地
Overview of Risk Assessment and Management for Intelligent Systems under the AI Act and Beyond
- 构建覆盖技术到社会影响的AI风险谱系
- 总结通用风险评估框架与最佳实践
- 揭示研究空白，指导未来方向
社会及新兴的基于风险的AI监管框架凸显了严格风险评估对保障AI系统安全可靠的重要性。为此，本文综述了AI风险评估（识别与分析）和管理的方法论。首先回顾全球监管格局，说明系统性风险评估的必要性；随后梳理文献中识别的各类AI相关风险，涵盖技术故障至伦理与社会影响；接着评述面向AI系统的主流风险评估方法，聚焦通用框架；最后提炼最佳实践，揭示方法学缺口，指明未来研究重点。
原文摘要 · Abstract (English)
The society and emerging risk-based regulatory frameworks for AI underscore the need for rigorous risk assessment to ensure safe and reliable AI systems. In response to this imperative, this paper presents an overview of AI risk assessment (identification and analysis) and management methodologies. It begins by reviewing the worldwide regulatory landscape that drives the need for systematic AI risk assessment. Then we characterize the spectrum of AI-related risks identified in the literature, from technical failures to ethical and social impacts. Subsequently, it reviews key risk assessment methodologies proposed for AI systems, focusing on general frameworks. The paper highlights best practices and illuminates methodological gaps, highlighting areas for further research on AI risk assessment.
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