MEASURE 3.1 Tracking existing and emergent risks
Approaches, personnel and documentation to regularly identify and track existing, unanticipated and emergent AI risks based on factors such as intended and actual performance in deployed contexts.
MEASURE 3 Tracking AI risks over time
Tracking AI risks after deployment: existing and emergent risks, risks that current methods cannot measure, and end user problem reporting and appeals.
MEASURE 3.2 Risks that are hard to measure
Considering risk tracking approaches for settings where AI risks are hard to assess with current measurement techniques or where metrics do not yet exist.
MEASURE 3.3 End user problem reporting and appeals
Feedback processes that let end users and impacted communities report problems and appeal system outcomes, integrated into AI system evaluation metrics.
