HUMHUM-003 — Human-AI Collaboration Design Flaws
LLM Knowledge Boundary Gaps Drive Hallucination Risk Across Deployments
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
Large language models cannot encode all world knowledge and struggle with rare or specialist information, producing confident but false outputs. Organisations deploying LLMs in high-stakes domains face material liability where hallucinated content informs decisions.
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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