HUMHUM-003 — Human-AI Collaboration Design Flaws
LLM Fails to Recall Memorised Facts Despite Storing Them
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
Large language models store training data but systematically fail to retrieve it accurately due to co-occurrence bias, positional artefacts, and duplicate records. Organisations relying on LLMs for knowledge retrieval face material risk of confident, undetected errors in high-stakes outputs.
Domain
Human Factors
Blindspots in change management, skills, human-AI collaboration, trust, workforce, and culture.
Source
MIT AI Risk Repository — Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024) ↗https://airisk.mit.edu/
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