NIST AI RMF Podcast 02 - NIST Generative AI Risk Management (AI 600-1 )

This podcast explores the core elements of NIST AI 600-1, a framework designed to help organizations identify, measure, and manage the unique and often amplified risks associated with generative AI systems. It highlights twelve central risk areas, including confabulation, dangerous or violent content, data privacy concerns, environmental impact, harmful and systemic bias, human–AI configuration challenges, information security threats, intellectual property risks, obscene or abusive outputs, and vulnerabilities across the AI value chain. The discussion also focuses on practical, cross-sector, and voluntary actions organizations can take to govern, map, measure, and manage these risks effectively. Special emphasis is placed on pre-deployment testing, content provenance mechanisms such as watermarking and tracking, and strong incident reporting processes to ensure accountability. Throughout, the podcast aligns these efforts with the AI Risk Management Framework’s four core functions—Govern, Map, Measure, and Manage—promoting greater trust, security, and safety in the deployment of generative AI technologies.