Why Linguistics Will Thrive in the 21st Century: A Reply to Piantadosi
  (2023)
Jordan Kodner Sarah Payne Jeffrey Heinz
We present a critical assessment of Piantadosi's (2023) claim that "Modern
language models refute Chomsky's approach to language," focusing on four main
points. First, despite the impressive performance and utility of large language
models (LLMs), humans achieve their capacity for language after exposure to
several orders of magnitude less data. The fact that young children become
competent, fluent speakers of their native languages with relatively little
exposure to them is the central mystery of language learning to which Chomsky
initially drew attention, and LLMs currently show little promise of solving
this mystery. Second, what can the artificial reveal about the natural? Put
simply, the implications of LLMs for our understanding of the cognitive
structures and mechanisms underlying language and its acquisition are like the
implications of airplanes for understanding how birds fly. Third, LLMs cannot
constitute scientific theories of language for several reasons, not least of
which is that scientific theories must provide interpretable explanations, not
just predictions. This leads to our final point: to even determine whether the
linguistic and cognitive capabilities of LLMs rival those of humans requires
explicating what humans' capacities actually are. In other words, it requires a
separate theory of language and cognition; generative linguistics provides
precisely such a theory. As such, we conclude that generative linguistics as a
scientific discipline will remain indispensable throughout the 21st century and
beyond.