Independent runtime checks that observe AI decisions and trigger alerts or interventions when policies or thresholds are violated.
A secondary monitoring layer - implemented as separate services or processes - that inspects model outputs in real time against predefined rules (e.g., forbidden content, out-of-range predictions). When violations occur, watchdogs can automatically block the decision, escalate to human review, or rollback to a safe model version. Governance defines watchdog policies, response SLAs, and logging requirements for forensic analysis.
A content-moderation AI is complemented by a watchdog service that scans every approved post for hate-speech patterns. If any flagged term slips through, the watchdog immediately retracts the post and opens an incident ticket for the moderation team - providing a safety net against model errors.
