Classification
AI Risk Management & Governance
Overview
The Core Functions-Govern, Map, Measure, and Manage-form the foundational pillars of the NIST AI Risk Management Framework (RMF). 'Govern' establishes organizational policies, roles, and accountability structures for AI risk management. 'Map' focuses on understanding AI systems, their intended context, and identifying relevant risks. 'Measure' involves assessing and tracking risks, impacts, and system performance using qualitative and quantitative methods. 'Manage' refers to implementing risk controls, monitoring effectiveness, and adapting to new information. These functions are iterative and interconnected, supporting a lifecycle approach to AI risk management. A core limitation is that effective implementation depends on organizational maturity and resource availability, and the RMF does not prescribe specific technical controls, requiring organizations to tailor practices to their context. Additionally, ambiguity in risk definitions and prioritization can lead to inconsistent application.
Governance Context
The Core Functions are operationalized through concrete obligations in governance frameworks such as the NIST AI RMF and the EU AI Act. For example, 'Govern' requires organizations to establish clear roles, responsibilities, and accountability mechanisms for AI oversight (NIST AI RMF, Function 1.1; EU AI Act, Article 9 on risk management systems). 'Measure' obligates organizations to conduct regular impact assessments and document risk evaluation processes (NIST AI RMF, Function 3.2; EU AI Act, Article 29 on post-market monitoring). Additional controls include maintaining comprehensive documentation of risk management activities and establishing incident response procedures. Frameworks like ISO/IEC 23894:2023 further specify requirements for risk monitoring, incident response, and documentation, reinforcing the need for continuous improvement and transparency. Organizations are also expected to align their practices with sector-specific regulations and standards where applicable.
Ethical & Societal Implications
The core functions promote ethical AI by embedding accountability, transparency, and continuous risk assessment. Effective governance can prevent harms such as discrimination, privacy violations, and safety hazards. However, if these functions are superficially implemented or lack stakeholder input, they may fail to detect or mitigate systemic risks, perpetuating social inequities. Balancing innovation with robust risk controls is essential to maintain public trust and comply with evolving legal standards.
Key Takeaways
The four core functions-Govern, Map, Measure, Manage-structure AI risk management activities.; These functions are iterative, interconnected, and adaptable to organizational context.; Governance frameworks like NIST AI RMF and EU AI Act operationalize these functions with concrete controls.; Effective implementation requires organizational maturity, ongoing assessment, and stakeholder engagement.; Limitations include resource constraints, ambiguity in risk definitions, and potential for inconsistent application.