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NIST AI RMF · Subcategory 2.1

Test sets, metrics, and details about the tools used during test, evaluation, validation, and verification (TEVV) are documented.

Summary

Test sets, metrics, and details about the tools used during test, evaluation, validation, and verification (TEVV) are documented.

documentationtevvvalidity and reliability

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

← Subcategory 2.1

The specific task, and methods used to implement the task, that the AI system will support is defined (e.g., classifiers, generative models, recommenders).

Subcategory 2.2 →

The organization’s personnel and partners receive AI risk management training to enable them to perform their duties and responsibilities consistent with related policies, procedures, and agreements.

Track NIST AI RMF subcategory 2.1 as evidence

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Subcategory 1.1

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

Subcategory 1.1

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.

Subcategory 1.1

Intended purpose, potentially beneficial uses, context-specific laws, norms and expectations, and prospective settings in which the AI system will be deployed are understood and documented. Considerations include: specific set or types of users along with their expectations; potential positive and negative impacts of system uses to individuals, communities, organizations, society, and the planet; assumptions and related limitations about AI system purposes; uses and risks across the development or product AI lifecycle; TEVV and system metrics.

Subcategory 1.1

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.