OPSOPS-001 — Monitoring and Alerting Inadequacies
LLMs Misled by Irrelevant Context, Degrading Reliable Performance
4/5Sector: TechnologyGeography: GlobalStage: OperateIngested: —
Executive Summary
Large language models show significant performance drops when exposed to irrelevant contextual information, including under structured prompting techniques. Organisations deploying LLMs in operational workflows face unreliable outputs without robust input governance and prompt validation controls.
Domain
Operational Management
Blindspots in monitoring, incident response, performance, scalability, integration, and business continuity.
Source
MIT AI Risk Repository — Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems (Gipiškis2024) ↗https://airisk.mit.edu/
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