Abstract
Abstract Recent advances in philosophical thinking about consciousness, such as cognitive phenomenology and mereological analysis, provide a framework that facilitates using computational models to explore issues surrounding the nature of consciousness. Here we suggest that, in particular, studying the computational mechanisms of working memory and its cognitive control is highly likely to identify computational correlates of consciousness and thereby lead to a deeper understanding of the nature of consciousness. We describe our recent computational models of human working memory and propose that three computational correlates of consciousness follow from the results of this work: itinerant attractor sequences, top-down gating, and very fast weight changes. Our current investigation is focused on evaluating whether these three correlates are sufficient to create more complex working memory models that encompass compositionality and basic causal inference. We conclude that computational models of working memory are likely to be a fruitful approach to advancing our understanding of consciousness in general and in determining the long-term potential for development of an artificial consciousness specifically.
Highlights
Recent advances in philosophical thinking about consciousness, such as cognitive phenomenology and mereological analysis, provide a framework that facilitates using computational models to explore issues surrounding the nature of consciousness
We argue here that working memory and the cognitive control mechanisms associated with it provide an excellent context in which to search for computational correlates of consciousness
According to cognitive phenomenology, working memory and the cognitive control of working memory provide an appropriate context in which to search for computational correlates of consciousness
Summary
It is easy to dismiss most work done in artificial intelligence (AI) and computational modeling in general as irrelevant to the mind-body problem and, to the study of consciousness or to assessing the prospects for creating a conscious machine. Prentner has recently argued within the framework of process metaphysics that re-conceiving phenomenal consciousness in the context of mereology could be an effective way to elucidate its nature.[10] In other words, rather than viewing consciousness as composed of qualia that are non-structured properties of subjective experience, consciousness and its constitution should be understood in terms of a mereological analysis of internallystructured processes This mereological approach provides a potential bridge between philosophical issues surrounding the hard problem and methodologies already used in AI cognitive models, and more generally suggests to us that investigating the structure of cognitive processes might lead to useful insights about consciousness.
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