OPSOPS-001 — Monitoring and Alerting Inadequacies
AI System Fails When Operational Data Diverges From Test Distribution
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
An AI system tested on approximated data distributions can behave unreliably when real operational data deviates unexpectedly from those assumptions. Organisations face undetected performance degradation in live deployments without systematic post-deployment data monitoring.
Domain
Operational Management
Blindspots in monitoring, incident response, performance, scalability, integration, and business continuity.
Source
MIT AI Risk Repository — AI Hazard Management: A Framework for the Systematic Management of Root Causes for AI Risks (Schnitzer2024) ↗https://airisk.mit.edu/
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