Do language models lack communicative intentions?

Abstract In some recent work, some psychologists, linguists, AI researchers, and philosophers (e.g., Shanahan, 2022; Bender & Koller, 2020; Montemayor, 2021; Bender et al., 2021) have argued that, despite producing convincing human-like linguistic output, large language models do not possess linguistic competence on the ground that they lack communicative intention. Among the proponents of this position, the notion of communicative intention is entertained as the liveliest candidate for a distinguishing characteristic of human cognition vis-a-vis LLMs and as such as at least one of the features which accounts for the characteristic mentality of humans. I demonstrate that such a position is largely driven by strong Gricean assumptions about the nature of linguistic competence that I argue is now known to be empirically untenable. Moreover, I show that once we give up these assumptions and fairly assess the architecture of both LLM and human cognitive architectures, we will find no good reasons to suppose large language models lack communicative intentions. I thus reject communicative intentions as a viable ground on which to understand the difference between LLMs and humans and thus as a characteristic mark of human mentality.