NIST AI RMF

What is NIST AI RMF?

The NIST AI Risk Management Framework (AI RMF) was developed to help organizations better identify and manage the risks associated with AI technology.  First published in 2023, the NIST AI RMF is a voluntary, high-level framework that is industry-agnostic and applicable to various types of AI systems. The implementation of the NIST AI RMF framework will allow organizations to design, develop, deploy, and use trustworthy AI systems that operate safely and ethically.

According to NIST, these are the characteristics of trustworthy AI:

• Valid and Reliable: The AI system should consistently perform as expected by being accurate, robust, and dependable under expected conditions.
• Safe: AI systems should not endanger human life, health, property, or the environment. Safety considerations must be taken into consideration throughout the entire system lifecycle.
• Secure and Resilient: The system should be able to withstand unexpected adverse events or unexpected changes in its environment. Secure systems can maintain confidentiality, integrity, and availability through protection mechanisms that prevent unauthorized access.
• Accountable and Transparent: To ensure accountability, organizations must maintain practices and governing structures for harm reduction and risk management. Information about an AI system should be readily accessible to users.
• Explainable and Interpretable: Users and stakeholders should be able to understand how the system operates and why it makes its outputs or decisions.
• Privacy-Enhanced: AI systems need to value user privacy, including anonymity and confidentiality. Methods such as data minimization and de-identification should be used to protect privacy.
• Fair – with Harmful Bias Managed: AI systems must account for concerns about harmful bias and discrimination. NIST identifies three categories of AI bias to be managed: Systemic, statistical, and cognitive.

Four functions serve as the foundation for NIST AI RMF: Govern, Map, Measure, and Manage. Each function is comprised of categories and subcategories with specific actions and outcomes.

• The Govern function helps organizations develop a culture of AI risk management by outlining methods to identify and account for the risks posed by an AI system.
• The Map function concentrates on managing risks found in every phase of an AI system’s lifecycle, including assessing potential risks to all stakeholders and end-users.
• The Measure function guides the development of quantitative and qualitative methods to assess AI risks and impacts.
• The Manage function focuses on dedicating resources to mitigate the identified risks and developing incident response plans.

Achieving NIST AI RMF Compliance

Here are some steps organizations can take to develop and deploy AI systems that are compliant with NIST AI RMF.

• Form an AI risk oversight group to establish roles and responsibilities for the implementation of compliant AI systems. The group should include technical, legal, compliance, and business stakeholders.
• Inventory and classify all AI systems in development or production, including those embedded in vendor products. Classify them based on criticality, intended use, and potential for harm to prioritize which systems to assess first.
• Define your organization’s tolerance for AI risk in areas such as fairness, privacy, safety, and robustness. This will help your business strike a balance between innovation and risk mitigation for AI development and use.
• Map each system’s purpose, data sources, user groups, and potential non-user stakeholders who could be impacted. Identify where harm could occur in data handling, model outputs, or misuse scenarios.
• Define risk metrics for your organization that enable the measurement of the potential impacts of bias detection, privacy vulnerabilities, etc. Integrate these into development workflows so measurement happens continuously.
• Develop and implement technical and procedural safeguards like bias mitigation techniques, human review processes, and incident response triggers. Align each control to a specific identified risk.
• Create a monitoring program to detect system flaws such as data drift, unusual input patterns, or performance degradation. Continually update your program to account for changes to the environment and emerging risks.

To be able to demonstrate NIST AI RMF compliance to customers and partners, maintain comprehensive documentation of your AI governance and risk management processes, including risk assessments, testing results, and mitigation strategies.

NIST has a library of resources available to help organizations successfully implement the AI RMF framework.

• The NIST AI RMF Playbook provides suggested steps organizations can take to achieve the outcomes laid out in the framework’s Core categories.
• Use cases document AI RMF implementations in government, industry, and academia.
• Crosswalk documents are available to provide a mapping of concepts and terms between the AI RMF and other guidelines and frameworks.
• The Roadmap outlines NIST’s priorities for updating the framework to account for gaps in knowledge, practice, or guidance as AI technology advances and the adoption of AI systems becomes more widespread.
• The NIST Trustworthy and Responsible Artificial Intelligence Resource Center (AIRC) is a platform to support people and organizations in government, industry, and academia, driving technical and scientific innovation in AI.

Benefits of NIST AI RMF Compliance

NIST AI RMF compliance allows businesses to demonstrate their commitment to using AI ethically and safely, while simultaneously getting ahead of AI regulations. Implementing NIST AI RMF standards can serve as a strong foundation for compliance with the EU AI Act and other AI laws by embedding risk-based governance, transparency, and oversight practices into AI development and deployment.

How We Can Help

CompliancePoint has a team of experts who specialize in NIST standards. We can help your organization design and implement safeguards that will help you leverage AI systems that are compliant with NIST AI RMF.