How Linguistics Learned to Stop Worrying and Love the Language Models

What can fluent language models tell us about linguistic structure and human language learning? Kyle Mahowald evaluates two opposing positions: that models do not learn language in a way relevant to people, and that their success makes linguistic theory unnecessary. Drawing on a position paper with Richard Futrell, he argues that language models provide useful evidence about structure, processing and acquisition while leaving an essential role for theory. The talk examines grammaticality judgments in language models and controlled pretraining experiments in which small models learn from systematically manipulated corpora. These methods allow researchers to revisit claims about learning and identify which properties of the input support linguistic generalisation.