Large Language Models and the Enhancement of Human Cognition: Some Theoretical Insights

Abstract

This essay explores the possible contribution of Large Language Models (LLMs) to human cognition. It investigates whether human cognition can be enhanced by advanced AI systems such as LLMs. Can LLMs make people as learners smarter, or, on the contrary, make them reason/think less? The author discusses the concepts of human and artificial intelligence and examines LLMs as advanced AI systems, which use deep learning techniques and can be considered as excelling in neural network architectures, data volume, generalisation and scalability. The author suggests that while LLMs can assist in facilitating numerous cognitive tasks, more research and philosophical inquiry is needed to understand whether such kind of AI assistance would make people cultivate human intelligence more, and not less. Presumably, Large Language Models (LLMs) can contribute to human intelligence and cognition just under strict (addressed existing limitations, questioning prompting, time-sensitivity, etc.) conditions. However, it is important that these theoretical considerations could be verified by experimental research.