Researchers argue the term 'hallucination' is overused and imprecise for describing AI errors, calling for more nuanced terminology.

The blanket use of 'hallucination' obscures different types of AI failures and their underlying causes

More precise language would help distinguish between factual errors, logical inconsistencies, and other AI mistakes

Better terminology could improve how developers debug and address specific failure modes in language models

The article advocates for a shift away from vague language toward more technical and descriptive error classification