NIST AI Risk Management Framework in Practice
Blog post from Galileo
The NIST AI Risk Management Framework (AI RMF) 1.0, developed by the National Institute of Standards and Technology, is a voluntary framework for identifying, measuring, and managing AI risks across the lifecycle, structured around four core functions: Govern, Map, Measure, and Manage. It aims to provide a continuous loop for AI risk management, addressing the challenges posed by autonomous agents, which differ from traditional models by making non-deterministic, multi-step decisions with real-world implications. The framework emphasizes creating a culture of governance, ensuring traceability and accountability through centralized policy enforcement, and employing production-grade metrics to capture unique failure modes of autonomous systems. It also facilitates operational control by integrating continuous monitoring and real-time enforcement of safety and compliance standards, thereby allowing organizations to manage AI risks proactively and effectively. The framework is adaptable for various domains, with specific profiles like the Generative AI Profile helping tailor risk management strategies to unique sector requirements, such as those in banking and healthcare, ensuring the AI systems' trustworthiness and compliance at all levels.