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On the compatibility of generative AI and generative linguistics

Nature Computational Science volume 5, pages 745–753 (2025)Cite this article

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Abstract

Chomsky’s generative linguistics has made substantial contributions to cognitive science and symbolic artificial intelligence. With the rise of neural language models, however, the compatibility between generative artificial intelligence and generative linguistics has come under debate. Here we outline three ways in which generative artificial intelligence aligns with and supports the core ideas of generative linguistics. In turn, generative linguistics can provide criteria to evaluate and improve neural language models as models of human language and cognition.

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Fig. 1: Example of context-free generative grammar.
Fig. 2: The Chomsky–Schützenberger hierarchy.
Fig. 3: Example of structural ambiguity in RGs and CFGs.
Fig. 4: Development procedures and adequacy of linguistic models.
Fig. 5: Comparison of transformer-based LLMs and grammar induction LMs in terms of prior assumptions and training outputs.
Fig. 6: Intuitive grammar induction example.

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Acknowledgements

E.P. thanks the participants and panelists of the Université du Québec á Montréal (UQÁM)’s Institut des Sciences Cognitives 2024 Summer School Chatting Minds: The Science and Stakes of Large Language Models, where the idea for this piece originally took form. This research was supported by E.P.’s IVADO Professor program.

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  1. Department of Decision Sciences, HEC, Montréal, Québec, Canada

    Eva Portelance

  2. Mila - Québec Artificial Intelligence Institute, Montréal, Québec, Canada

    Eva Portelance

  3. Department of Linguistics, University of California – Davis, Davis, CA, USA

    Masoud Jasbi

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  1. Eva Portelance
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  2. Masoud Jasbi
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Both E.P. and M.J. contributed to the conceptualization and writing of this paper.

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Correspondence to Eva Portelance.

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Portelance, E., Jasbi, M. On the compatibility of generative AI and generative linguistics. Nat Comput Sci 5, 745–753 (2025). https://doi.org/10.1038/s43588-025-00861-2

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