Cognitive Computation

, Volume 1, Issue 3, pp 221–233 | Cite as

A Cognitive Computation Fallacy? Cognition, Computations and Panpsychism

Article

Abstract

The journal of Cognitive Computation is defined in part by the notion that biologically inspired computational accounts are at the heart of cognitive processes in both natural and artificial systems. Many studies of various important aspects of cognition (memory, observational learning, decision making, reward prediction learning, attention control, etc.) have been made by modelling the various experimental results using ever-more sophisticated computer programs. In this manner progressive inroads have been made into gaining a better understanding of the many components of cognition. Concomitantly in both science and science fiction the hope is periodically re-ignited that a man-made system can be engineered to be fully cognitive and conscious purely in virtue of its execution of an appropriate computer program. However, whilst the usefulness of the computational metaphor in many areas of psychology and neuroscience is clear, it has not gone unchallenged and in this article I will review a group of philosophical arguments that suggest either such unequivocal optimism in computationalism is misplaced—computation is neither necessary nor sufficient for cognition—or panpsychism (the belief that the physical universe is fundamentally composed of elements each of which is conscious) is true. I conclude by highlighting an alternative metaphor for cognitive processes based on communication and interaction.

Keywords

Computationalism Machine consciousness Panpsychism 

Notes

Acknowledgments

I would like to thank the reviewers for the many helpful comments I received during the preparation of this article. I would also like to thank Ron Chrisley for his many interesting criticisms regarding the DwP reductio. Lastly I would like to thank Slawek Nasuto and Kris de Meyer for their foundational work outlining a new ‘swarm’ metaphor for cognition based on communication and its subsequent analysis within the framework of stochastic diffusion search.

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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Department of Computing, GoldsmithsUniversity of LondonLondonUK

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