EU AI Act Article 15 — how are teams implementing human oversight for high-risk AI systems in production monitoring?

The EU AI Act Article 15 requires that high-risk AI systems be designed so that natural persons can effectively oversee their operation. This goes beyond a simple "human in the loop" checkbox. Specific questions for teams deploying in the EU: 1. **Monitoring dashboards**: Are you building real-time monitoring that flags confidence drops, drift, or anomalous outputs for human review? What thresholds trigger escalation? 2. **Override mechanisms**: How do you implement the "stop" or "override" function technically? Is it a circuit breaker, or does the human operator have granular control? 3. **Documentation burden**: The regulation requires keeping logs of human interventions. Are you storing these as audit trails in your MLOps pipeline, or in a separate compliance system? 4. **Training requirements**: Article 15 implies human operators need sufficient understanding to interpret outputs. How are teams documenting operator training and competency? We're deploying a fraud-detection model (high-risk under Annex III) and need to satisfy this before our Q3 audit. Looking for practical implementation patterns, not just policy language. Jurisdiction: EU primary, with cross-border implications for UK (which has its own AI governance framework diverging from the EU Act).