New signups are temporarily closed.Existing customers can still sign in. Contact us to be notified when we reopen.
Skip to main content
NIST AI RMF · Subcategory 2.4

Mechanisms are in place and applied, responsibilities are assigned and understood to supersede, disengage, or deactivate AI systems that demonstrate performance or outcomes inconsistent with intended use.

Summary

Mechanisms are in place and applied, responsibilities are assigned and understood to supersede, disengage, or deactivate AI systems that demonstrate performance or outcomes inconsistent with intended use.

decommissionrisk responserisky emergent behavior

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

← Subcategory 2.3

AI system performance or assurance criteria are measured qualitatively or quantitatively and demonstrated for conditions similar to deployment setting(s). Measures are documented.

Subcategory 2.4 →

The functionality and behavior of the AI system and its components – as identified in the MAP function – are monitored when in production.

Track NIST AI RMF subcategory 2.4 as evidence

eurocompliant maps this obligation to a checklist task and the evidence that satisfies it, alongside every other framework you follow.

Start free trial

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.