What Is AI Hallucination?
Hallucination is when an AI model generates factually incorrect or fabricated content presented with the same confidence as accurate content. It is not a bug, it is a fundamental characteristic of how large language models work.
AI Hallucination, when a generative AI model produces content that is factually incorrect, fabricated, or unsupported by its training data while presenting it with the same confidence as accurate content.
Hallucination is not a bug, it is a structural characteristic of how large language models work. They predict plausible next tokens, not verified facts. The implications differ sharply by context: a fabricated case citation in legal filings can trigger court sanctions (Mata v Avianca, 2023); a fabricated drug interaction in clinical use is life-threatening; a fabricated regulatory reference in a submission creates serious compliance exposure. RAG (retrieval-augmented generation) reduces hallucination by grounding outputs in verified sources, but does not eliminate it.
Source: Mata v Avianca (2023); NIST AI 600-1 (Generative AI Profile)