Flag high risk outputs

Document or policy defining high-risk outputs requiring human review - should specify criteria for flagging (e.g. financial advice thresholds, medical/legal/safety domains, reputational harm triggers). Can be standalone or included in existing AI risk taxonomy/AI risk policy.

Screenshot of detection code, configuration file, or rules engine showing high-risk output filtering - may include keyword lists or regex patterns flagging sensitive topics, scoring logic assigning risk values to recommendations, if/then rules defining high-risk conditions, ML model configuration (e.g., classification thresholds in config.yaml), or API response showing confidence scores with risk thresholds.

Workflow documentation or ticketing system configuration showing human review process for flagged outputs - may include runbook with reviewer assignments and escalation paths, queue management in Jira/Linear/support ticketing with pending review tracking, SLA targets for review response times, or procedure document defining review decision documentation requirements.