OPSOPS-001 — Monitoring and Alerting Inadequacies
ML System Design Flaws Create Cascading Operational Failures
3/5Sector: OtherGeography: GlobalStage: DevelopIngested: —
Executive Summary
Poor problem framing and component-level design choices in ML systems introduce systemic failure risks beyond the model itself. Boards must treat pipeline architecture as a governance concern, not solely a technical one.
Domain
Operational Management
Blindspots in monitoring, incident response, performance, scalability, integration, and business continuity.
Source
MIT AI Risk Repository — The Risks of Machine Learning Systems (Tan2022) ↗https://airisk.mit.edu/
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