Hosted by JANUS Associates, this document was developed by NIST (National Institute of Technology and Standards). Artificial Intelligence Risk Management Framework (AI RMF 1.0) offers a path to minimize potential negative impacts of AI systems, such as threats to civil liberties and rights, while also providing opportunities to maximize positive impacts.

The Framework is designed to equip organizations and individuals – referred to here as AI actors – with approaches that increase the trustworthiness of AI systems and to help foster the responsible design, development, deployment, and use of AI systems over time. AI actors are defined by the Organization for Economic Co-operation and Development (OECD) as “those who play an active role in the AI system lifecycle, including organizations and individuals that deploy or operate AI.  The AI RMF is intended to be practical, to adapt to the AI landscape as AI technologies continue to develop, and to be operationalized by organizations in varying degrees and capacities so society can benefit from AI while also being protected from its potential harms.

The Framework is divided into two parts. Part 1 discusses how organizations can frame the risks related to AI and describe the intended audience. Next, AI risks and trustworthiness are analyzed, outlining the characteristics of trustworthy AI systems, which include valid and reliable, safe, secure and resilient, accountable and transparent, explainable and interpretable, privacy-enhanced, and fair with their harmful biases managed.

Part 2 comprises the “Core” of the Framework. It describes four specific functions to help organizations address the risks of AI systems in practice. These functions – GOVERN, MAP, MEASURE, and MANAGE – are broken down further into categories and subcategories. While GOVERN applies to all stages of organizations’ AI risk management processes and procedures, the MAP, MEASURE, and MANAGE functions can be applied in AI system-specific contexts and at specific stages of the AI lifecycle.

Additional resources related to the Framework are included in the AI RMF Playbook, which is available via the NIST AI RMF website: https://www.nist.gov/itl/ai-risk-management-framework.