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-2.11: Fairness and bias as identified in the MAP function is evaluated and results are documented

Fairness and bias – as identified in the MAP function – is evaluated and results are documented. Fairness evaluation states which fairness definition was applied and why, evaluates against it, and records the results including where the definition itself is contested.

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 3 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 · 1 control

ISO/IEC 42001:2023 · 1 control

  • A.7.4 Quality of data for AI systems

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-2.11 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.

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.