OPSOPS-001 — Monitoring and Alerting Inadequacies
Poor Training Data Quality Propagates Errors and Bias in Generative AI Outputs
4/5Sector: OtherGeography: GlobalStage: DevelopIngested: —
Executive Summary
Generative AI models replicate factual errors, imbalances, and biases present in their training data, degrading output reliability at scale. Organisations deploying such systems inherit data-quality risk directly into operational decisions and customer-facing outputs.
Domain
Operational Management
Blindspots in monitoring, incident response, performance, scalability, integration, and business continuity.
Source
MIT AI Risk Repository — Generative AI and ChatGPT: Applications, Challenges, and AI-Human Collaboration (Nah2023) ↗https://airisk.mit.edu/
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