Artificial Speech Acts

Abstract Can Large Language Models (LLMs) perform speech acts? I show how a norm-based argument against LLM-assertion can be generalized so as to support a negative answer to this question. I then investigate how the resulting no-speech-act-view interacts with several other debates about how to conceptualize the linguistic outputs of LLMs. I argue that it conflicts with the popular conception of LLMs as bullshitters and that it helps decide between two competing externalist accounts of how artificially generated expressions refer. I close by discussing a challenge to the no-speech-act-view and by suggesting a novel strategy for addressing it. A general lesson from this discussion is that our understanding of LLMs' linguistic outputs will profit from complementing extant meta-semantic theorizing with more detailed meta-pragmatic theorizing about discourse between humans and LLMs.

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Journal
Analysis
Published
2026-04-01
DOI
https://doi.org/10.1093/analys/anag022
Primary Topic
Computational and Text Analysis Methods
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial Speech Acts

Lukas Skiba
Analysis
Computational and Text Analysis Methods
article

Artificial Speech Acts

Lukas Skiba
article en

Abstract

Abstract Can Large Language Models (LLMs) perform speech acts? I show how a norm-based argument against LLM-assertion can be generalized so as to support a negative answer to this question. I then investigate how the resulting no-speech-act-view interacts with several other debates about how to conceptualize the linguistic outputs of LLMs. I argue that it conflicts with the popular conception of LLMs as bullshitters and that it helps decide between two competing externalist accounts of how artificially generated expressions refer. I close by discussing a challenge to the no-speech-act-view and by suggesting a novel strategy for addressing it. A general lesson from this discussion is that our understanding of LLMs' linguistic outputs will profit from complementing extant meta-semantic theorizing with more detailed meta-pragmatic theorizing about discourse between humans and LLMs.

Analysis
University of Bergen (NO)
Openalex Percentile: Top 14%
Computational and Text Analysis Methods
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