Monitoring algorithm performance is crucial to ensure that the organization sustains the desired level of operational performance. The monitoring must be systematic and metrics-based to achieve consistency over time.
The AI System Owner should ensure that the organization defines, documents, and implements
1) workflows and technical interfaces to facilitate the monitoring of AI system performance, including for example
2) automated or manual production and reporting of performance metrics data,
3) alarm thresholds, and
4) workflows that allocate monitoring responsibilities.
5) workflows to address issues detected during regular monitoring and health checks.
The Algorithm Owner should ensure that the AI system performance monitoring design process aligns with the organization’s values and risk tolerance.