Conversational Agents and the Understanding of Human Language: Reflections on AI, LLMs, and Cognitive Science
For cognitive scientists and linguists, this paper argues that current AI language models do not contribute to understanding human cognition, but the claim is not novel.
The paper reviews the evolution of NLP from early approaches to large language models, concluding that despite advances in chatbot performance, these technologies have not significantly improved our understanding of human language processing.
In this paper, we discuss the relationship between natural language processing by computers (NLP) and the understanding of the human language capacity, as studied by linguistics and cognitive science. We outline the evolution of NLP from its beginnings until the age of large language models, and highlight for each of its main paradigms some similarities and differences with theories of the human language capacity. We conclude that the evolution of language technology has not substantially deepened our understanding of how human minds process natural language, despite the impressive language abilities attained by current chatbots using artificial neural networks.