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

TL;DR

This paper examines the relationship between NLP advancements, especially large language models, and human language understanding, highlighting that technological progress has not significantly deepened our cognitive understanding.

Contribution

It provides a reflective analysis comparing NLP paradigms with linguistic and cognitive science theories, emphasizing the gap in understanding human language processing.

Findings

NLP evolution parallels some linguistic theories but lacks insight into human cognition.

Current chatbots demonstrate impressive language abilities without deep understanding.

Technological progress has not substantially advanced understanding of human language processing.

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.