In artificial intelligence, a hallucination is an output that is fluent and confident but factually wrong, fabricated or unsupported by any source. A hallucinating chatbot may invent statistics, cite academic papers or court cases that do not exist, attribute made-up quotes to real people or describe product features that were never released – all in perfectly plausible language.
Hallucinations happen because of how large language models work. An LLM does not look facts up in a database; it generates the statistically most likely next word based on patterns learned during training. When the model lacks reliable knowledge about a topic, the most probable-sounding continuation can be entirely false. The confident tone is part of the problem: the model presents guesses and facts with the same fluency.
Common causes and contributing factors include:
- Gaps or errors in training data – The model cannot know events after its training cutoff or facts that were rare, wrong or missing in its data.
- Ambiguous or leading prompts – Questions that presuppose false information (“describe the 2019 merger between X and Y”) often get a fabricated answer rather than a correction.
- Optimization for helpfulness – Models trained to be agreeable and complete may prefer producing an answer over admitting uncertainty.
Strategies to reduce hallucinations include:
- Retrieval-augmented generation (RAG) – Connecting the model to a search engine, knowledge base or document store so answers are grounded in retrieved sources.
- Grounding and citations – Requiring the model to quote or link the sources behind each claim so users can verify them.
- Better prompting – Explicitly instructing the model to say “I don’t know” when unsure, and asking for sources.
- Human review – Keeping a person in the loop for high-stakes uses such as legal, medical and financial content.
Hallucination is the main reason AI-generated content should be fact-checked before publication, and reducing it remains one of the central open research problems in generative AI.
