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NIST AI RMF · Subcategory 2.1

Roles and responsibilities and lines of communication related to mapping, measuring, and managing AI risks are documented and are clear to individuals and teams throughout the organization.

Summary

Roles and responsibilities and lines of communication related to mapping, measuring, and managing AI risks are documented and are clear to individuals and teams throughout the organization.

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

← Subcategory 1.7

Processes and procedures are in place for decommissioning and phasing out of AI systems safely and in a manner that does not increase risks or decrease the organization’s trustworthiness.

Subcategory 2.1 →

Resources required to manage AI risks are taken into account, along with viable non-AI alternative systems, approaches, or methods – to reduce the magnitude or likelihood of potential impacts.

Track NIST AI RMF subcategory 2.1 as evidence

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More from NIST AI RMF

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.