This Letter responds to the ongoing debate on the terminology for large language model errors by arguing that “hallucination” mislocates the error in the perceptual domain and that “confabulation” is a better-calibrated conceptual borrowing. It further proposes a functional typology distinguishing ordinary from delusional confabulation, with practical implications for clinical settings.
Borrowing Carefully — The Words We Choose for AI Errors Shape Clinical Trust / Vannacci, Alfredo. - In: NEJM AI. - ISSN 2836-9386. - ELETTRONICO. - 3:(2026), pp. 0-0. [10.1056/ailtr2600282]
Borrowing Carefully — The Words We Choose for AI Errors Shape Clinical Trust
Vannacci, Alfredo
2026
Abstract
This Letter responds to the ongoing debate on the terminology for large language model errors by arguing that “hallucination” mislocates the error in the perceptual domain and that “confabulation” is a better-calibrated conceptual borrowing. It further proposes a functional typology distinguishing ordinary from delusional confabulation, with practical implications for clinical settings.File in questo prodotto:
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