Metacognitive Closure and Consciousness in Large Language Models

Abstract

Metacognition is an important aspect of information processing in the brain, subserving judgement and making cognition robust. In the literature, there are different views on the role metacognition plays in consciousness. The role of meta-cognition has been addressed by various studies. In relation to consciousness, some authors argue that metacognition is not necessarily essential in consciousness, but rather an extra mechanism constructed on a more basic mechanism, necessary when reflecting on and reporting one's own experiences. Others hold that metacognition is an integral part of phenomenal consciousness, possibly accounting for the hard problem of consciousness eventually. We aim to clarify why no consensus has been reached on whether large language models can possess consciousness, and why diverse and competing posi-tions persist regarding the nature and plurality of conscious-ness. On the strength of the analysis, we propose metacognitive closure, a concept analogous to Colin McGinn’s cognitive closure. We discuss the possibility that difficulties in elucidating mechanisms of consciousness might be clarified by considering the nature of metacognition. Based on this view, we argue how we may be able to streamline issues in consciousness through an analysis of metacognition, in a continuous spectrum with problems in cognition in general.