Cut the crap: a critical response to “ChatGPT is bullshit”
David J. Gunkel & Simon Coghlan
Abstract
In a recent thought-provoking essay called “ChatGPT is Bullshit,” Hicks, Humphries and Slater call such large language models (LLMs) “bullshitters” and “bullshit machines.” Unlike the term “bullshit,” they argue, commonly used anthropomorphic terms such as “hallucination” and “confabulation” mispresent LLMs and sow confusion that could be socially harmful. This paper criticizes their essay in two steps. First, its reliance on Harry Frankfurt’s classic characterization of bullshit as indifference to truth, though understandable and compelling in one sense, risks misrepresenting LLMs. Second, the argument is too quick to jettison anthropomorphic terms like hallucination and confabulation, which might prove useful metaphors for understanding generative AI. Exploring language to articulate good ways of understanding LLMs is indeed a socially important task, one benefitting from critical open-mindedness, some historical awareness, and a nuanced approach to how various words used to describe AI can operate. This paper attempts to contribute to this task by questioning the wisdom of categorically calling bullshit on ChatGPT.
10 citations
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.55 × 0.4 = 0.22 |
| M · momentum | 0.75 × 0.15 = 0.11 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.