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.
Summary
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.
Read the full official text: https://airc.nist.gov/airmf-resources/playbook/
← 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 1.2 →
The characteristics of trustworthy AI are integrated into organizational policies, processes, and procedures.
Track NIST AI RMF subcategory 1.1 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