HUMHUM-003 — Human-AI Collaboration Design Flaws
LLM Hallucination: Factual and Faithfulness Errors in Generated Content
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
Large language models systematically produce both factually incorrect outputs and content unfaithful to user-provided context, across summarisation, question-answering, and other tasks. Organisations deploying LLMs without detection controls face material liability from corrupted decisions and eroded stakeholder trust.
Domain
Human Factors
Blindspots in change management, skills, human-AI collaboration, trust, workforce, and culture.
Source
MIT AI Risk Repository — A Survey on Responsible LLMs: Inherent Risk, Malicious Use, and Mitigation Strategy (Wang2025) ↗https://airisk.mit.edu/
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