# [[AI Hallucination]]
![[AI Hallucination.svg]]
Hallucination in the context of [[Artificial Intelligence|AI]] refers to a common failure scenario for AI, in that it may begin to lose accuracy as it is fed more information. Hallucinations *sound* plausible, but are not grounded in facts.
Hallucinations occur when AI training data includes misleading, vague, or conflicting information.
## Hallucination Categories
The [[OpenLIT]] library includes a check for hallucination, in which it identifies four different "hallucination categories": [^openlit]
> - factual_inaccuracy: Incorrect facts, e.g., Context: ["Paris is the capital of France."]; Text: "Lyon is the capital."
> - nonsensical_response: Irrelevant info, e.g., Context: ["Discussing music trends."]; Text: "Golf uses clubs on grass."
> - gibberish: Nonsensical text, e.g., Context: ["Discuss advanced algorithms."]; Text: "asdas asdhasudqoiwjopakcea."
> - contradiction: Conflicting info, e.g., Context: ["Einstein was born in 1879."]; Text: "Einstein was born in 1875 and 1879."
[^openlit]: OpenLIT. `hallucination.py`, retrieved March 2025 from https://github.com/openlit/openlit/blob/main/sdk/python/src/openlit/evals/hallucination.py.
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