The Limitations of Large Language Models for Understanding Human Language and Cognition | Open Mind | MIT Press
Christine Cuskley, Rebecca Woods, Molly Flaherty; The Limitations of Large Language Models for Understanding Human Language and Cognition. Open Mind 2024; 8 1058–1083. doi: https://doi.org/10.1162/opmi_a_00160 Download citation file: Researchers have recently argued that the capabilities of Large Language Models (LLMs) can provide new insights into longstanding debates about the role of learning and/or innateness in the development and evolution of human language. Here, we argue on two grounds that LLMs alone tell us very little about human language and cognition in terms of acquisition and evolution. First, any similarities between human language and the output of LLMs are purely functional. Borrowing the “four questions” framework from ethology, we argue that what LLMs do is superficially similar, but how they do it is not. In contrast to the rich multimodal data humans leverage in interactive language learning, LLMs rely on immersive exposure to vastly greater quantities of unimodal
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