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 5.2

Mechanisms are established to enable AI actors to regularly incorporate adjudicated feedback from relevant AI actors into system design and implementation.

Summary

Mechanisms are established to enable AI actors to regularly incorporate adjudicated feedback from relevant AI actors into system design and implementation.

governanceimpact assessmentparticipation

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

← Subcategory 5.1

Likelihood and magnitude of each identified impact (both potentially beneficial and harmful) based on expected use, past uses of AI systems in similar contexts, public incident reports, feedback from those external to the team that developed or deployed the AI system, or other data are identified and documented.

Subcategory 5.2 →

Practices and personnel for supporting regular engagement with relevant AI actors and integrating feedback about positive, negative, and unanticipated impacts are in place and documented.

Track NIST AI RMF subcategory 5.2 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.