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NIST AI Risk Management Framework (AI RMF 1.0) & Trustworthy AI Architecture

Engineering valid, reliable, explainable, and privacy-preserving AI systems across Govern, Map, Measure, and Manage.

Executive Overview

The NIST AI Risk Management Framework (NIST AI RMF 1.0) provides organizations with practical guidance to address risks of AI systems, fostering the design, development, and deployment of trustworthy and responsible AI technologies.

1. The Four Core Functions: Govern, Map, Measure, Manage

The NIST AI RMF is structured around four iterative functions:

  • Govern: Cultivate a culture of risk management, establish accountability structures, and mandate AI safety policies.
  • Map: Identify the AI context, categorize operational use cases, and anticipate positive and negative societal impacts.
  • Measure: Employ quantitative and qualitative metrics to evaluate bias, accuracy, robustness, and cybersecurity resilience.
  • Manage: Allocate resources to identified AI risks, implement guardrails, and maintain continuous post-deployment monitoring.

Frequently Asked Questions

What characteristics define a 'Trustworthy AI' system according to NIST?

NIST defines trustworthy AI as valid and reliable, safe, secure and resilient, accountable and transparent, explainable and interpretable, privacy-enhanced, and fair with harmful bias managed.

AI Summary

The NIST AI Risk Management Framework (NIST AI RMF 1.0) provides organizations with practical guidance to address risks of AI systems, fostering the design, development, and deployment of trustworthy and responsible AI technologies.