NIST AI Risk Management Framework (AI RMF 1.0)
MEASURE - NIST AI RMF 1.0

NIST AI Risk Management Framework (AI RMF 1.0) AIRMF-MS-4.3: Measurable performance improvements or declines based on consultations with relevant AI actors including affected communities, and field data about context-relevant risks and trustworthiness characteristics, are identified and documented

Measurable performance improvements or declines based on consultations with relevant AI actors including affected communities, and field data about context-relevant risks and trustworthiness characteristics, are identified and documented. Change in performance over time is measured against a baseline using field data and consultation, so decline is detected as decline rather than absorbed as normal variation.

Maintained by Gerard BlokdykVerified against the published standard Control text last updated

What else in your programme already covers this

This control maps to 3 controls across 2 other frameworks. If you already hold one of them, the evidence you collected for it is the starting point here rather than new work.

EU AI Act · 2 controls

  • EUAI-Art.20 Corrective actions and duty of information
  • EUAI-Art.72 Post-market monitoring by providers and post-market monitoring plan for high-risk AI systems

ISO/IEC 42001:2023 · 1 control

  • A.6.2.6 AI system operation and monitoring

Every mapping shown was judged rather than inferred from wording similarity, and the ones that failed review are published too. See the coverage reports and what was rejected.

Other controls in MEASURE - NIST AI RMF 1.0

You are reading one control. How much of NIST AI Risk Management Framework (AI RMF 1.0) have you already done?

NIST AI Risk Management Framework (AI RMF 1.0) AIRMF-MS-4.3 is one control. If you already hold one of the frameworks below, a reviewed crosswalk already says how much of NIST AI Risk Management Framework (AI RMF 1.0) your existing evidence covers. Hold EU AI Act and 48 of 72 NIST AI Risk Management Framework (AI RMF 1.0) controls already carry evidence.

If you hold EU AI Act66.7% covered · 24 gapsIf you hold ISO/IEC 42001:202347.2% covered · 38 gaps

Each report names every control your existing framework evidences, every one it does not, the reasoning behind each claim, and the claims that were argued against and rejected. 10 were rejected on the EU AI Act pair alone.

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The graph holds this control, the 3 it maps to, and the evidence behind each claim, over MCP and REST.

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