Risk tracking approaches are considered for settings where AI risks are difficult to assess using currently available measurement techniques or where metrics are not yet available.
Summary
Risk tracking approaches are considered for settings where AI risks are difficult to assess using currently available measurement techniques or where metrics are not yet available.
Read the full official text: https://airc.nist.gov/airmf-resources/playbook/
← Subcategory 3.2
Potential costs, including non-monetary costs, which result from expected or realized AI errors or system functionality and trustworthiness - as connected to organizational risk tolerance - are examined and documented.
Subcategory 3.3 →
Targeted application scope is specified and documented based on the system’s capability, established context, and AI system categorization.
Track NIST AI RMF subcategory 3.2 as evidence
eurocompliant maps this obligation to a checklist task and the evidence that satisfies it, alongside every other framework you follow.
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