NIST AI Risk Management Framework (AI RMF 1.0) AIRMF-MS-4.2: Measurement results regarding AI system trustworthiness in deployment contexts and across the AI lifecycle are informed by input from domain experts and other relevant AI actors to validate whether the system is performing consistently as intended, and results are documented
Measurement results regarding AI system trustworthiness in deployment context(s) and across AI lifecycle are informed by input from domain experts and other relevant AI actors to validate whether the system is performing consistently as intended. Results are documented. Measured results are validated against the judgement of people who know the context, so a result inside its operational limits on paper is confirmed as adequate in practice.
Maintained by Gerard Blokdyk·Verified against the published standard ·Control text last updated
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This control maps to 1 controls across 1 other frameworks. If you already hold one of them, the evidence you collected for it is the starting point here rather than new work.
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