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. Engagement with affected actors is a resourced standing practice with named personnel, and unanticipated impacts have a route back into the impact record.
NIST AI Risk Management Framework (AI RMF 1.0) AIRMF-MP-5.2 is one control. If you already hold one of the frameworks below, a reviewed crosswalk already says how much of NIST AI Risk Management Framework (AI RMF 1.0) your existing evidence covers. Hold EU AI Act and 48 of 72 NIST AI Risk Management Framework (AI RMF 1.0) controls already carry evidence.
Each report names every control your existing framework evidences, every one it does not, the reasoning behind each claim, and the claims that were argued against and rejected. 10 were rejected on the EU AI Act pair alone.
The graph holds this control, the 0 it maps to, and the evidence behind each claim, over MCP and REST.