Overview of Risk Assessment and Management for Intelligent Systems under the AI Act and Beyond
For policymakers and AI developers, this overview synthesizes the landscape of AI risk assessment but offers no new empirical results or concrete numbers.
This paper reviews AI risk assessment and management methodologies in the context of emerging regulatory frameworks like the EU AI Act, characterizing AI-related risks and identifying gaps in current approaches.
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.