Development · Term
Hallucination
A hallucination is output from an AI model that is fluent and plausible but factually wrong — an invented citation, statistic, function, or quotation presented with the same confidence as correct information.
Hallucination is not a bug to be patched but a property of how generative models work: they produce statistically likely continuations, and likelihood is not truth. The practical danger is that a wrong answer looks exactly like a right one, so nothing in the writing itself signals which you are reading.
The mitigation is procedural rather than technical. Check every consequential claim against a primary source, open citations to confirm they support the statement beside them, and never let a model be the only reviewer of its own output.
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