Watchdog Monitoring
Independent runtime checks that observe AI decisions and trigger alerts or interventions when policies or thresholds are violated.
Definition
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.
Real-World Example
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.
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