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NIST AI RMF · Subcategory 2.13

Effectiveness of the employed TEVV metrics and processes in the MEASURE function are evaluated and documented.

Summary

Effectiveness of the employed TEVV metrics and processes in the MEASURE function are evaluated and documented.

effectivenesstevv

Read the full official text: https://airc.nist.gov/airmf-resources/playbook/

← Subcategory 2.12

Environmental impact and sustainability of AI model training and management activities – as identified in the MAP function – are assessed and documented.

Subcategory 3.1 →

Decision-makings related to mapping, measuring, and managing AI risks throughout the lifecycle is informed by a diverse team (e.g., diversity of demographics, disciplines, experience, expertise, and backgrounds).

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Subcategory 1.1

Legal and regulatory requirements involving AI are understood, managed, and documented.

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A determination is made as to whether the AI system achieves its intended purpose and stated objectives and whether its development or deployment should proceed.

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Approaches and metrics for measurement of AI risks enumerated during the Map function are selected for implementation starting with the most significant AI risks. The risks or trustworthiness characteristics that will not – or cannot – be measured are properly documented.