Conversational Agents and the Understanding of Human Language: Reflections on AI, LLMs, and Cognitive Science

Abstract

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.

Figures (1)

• Figure 1: Two simple structures of artificial neural networks that have been used to designed early neural language models. The core idea of such networks is that the activation of each unit is a function (often non linear) of the weighted sum of the activations of units connected to it.