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A Cognitive Computation Fallacy? Cognition, Computations and Panpsychism

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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.

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Notes

  1. In two earlier articles (with Nasuto et al. [11, 12]) the author explored theoretical limitations of the computational metaphor from positions grounded in psychology and neuroscience; this article—outlining a third perspective—reviews three philosophical critiques of the computational metaphor with respect to ‘hard’ questions of cognition related to consciousness and understanding. Its negative conclusion is that computation is neither necessary nor sufficient for cognition; its positive conclusion suggests that the adoption of a new metaphor may be helpful in addressing hard conceptual questions related to consciousness and understanding. Drawing on the conclusions of the two earlier articles, the suggested new metaphor is one grounding cognition in processes of communication and interaction rather than computation. An analogy is with the application of Newtonian physics and Quantum physics—both useful descriptions of the world, but descriptions that are most appropriate in addressing different types of questions.

  2. Controversy remains surrounding Descartes’ account of the representational content of non-intellectual thought such as pain.

  3. Although Putnam talks about pain not cognition, it is clear that his argument is intended to be general.

  4. For example, Lucas maintains a web page http://users.ox.ac.uk/~jrlucas/Godel/referenc.html listing more than 50 such criticisms.

  5. For early discussion of these themes see ‘Minds and Machines’, 4: 4, ‘What is Computation?’, November 1994.

  6. In [32], Chalmers critiques Putnam’s construction, noting that it fails to ensure that all states of the FSA are reliably transited; however, he subsequently demonstrates (ibid) that every physical system containing a ‘clock’ and a ‘dial’ will implement every input-less FSA.

  7. Although it is true that as the complexity of the logical system increases, the number of consistent computational functions that can be assigned to it diminishes, it remains the case that its computational properties will always be relative to the threshold logic value used; the physicalstate → computationalstate mapping will always determine the logical-function that the physical computational system instantiates.

  8. Cf. ‘What is a word-processor?’, in Winograd and Flores [59].

  9. The set of languages ‘acceptable’ by a stochastic automaton and a deterministic automaton is the same.

  10. “Suppose that a system exists whose activity through a period of time supports a mode of consciousness, e.g. a tickle or a visual sensum. The supervenience thesis tells us that, if we introduce into the vicinity of the system an entirely inert object that has absolutely no causal or physical interaction with the system, then the same activity will support the same mode of consciousness. Or again, if the activity of a system supports no consciousness, the introduction of such an inert and causally unconnected object will not bring any phenomenal state about if an active physical system supports a phenomenal state, how could the presence or absence of a causally disconnected object effect that state?” [22].

  11. In his article, ‘Counterfactual computational vehicles of consciousness’ [56] Chrisley states, “Bishop’s main mistake: claiming that differences in counterfactual behaviour do not constitute physical differences. Presumably, it is by virtue of some physical difference between a state of R 1(n) and the corresponding state of R 1(n+1) that gives the former a counterfactual property the latter lacks. Note that to delete the nth transition, one would have to physically alter R 1(n-1). So despite Bishop’s claim, if R 1 and R 2 differ in their counterfactual formal properties, they must differ in their physical properties. Causal properties (even counterfactual ones) supervene on physical properties.”

  12. It is also clear that in this case the ‘system as a whole’ (i.e. the environment, robot and VR and compiler) remains sensitive to counterfactuals—if we had pre-specified the experimental conditions to be a dull blue square, the partial evaluation compiler B would have modified object code accordingly—hence at the level of the system, Chalmers’ POI continues to apply. Interestingly, as this form of compile time partial evaluation process cannot be undertaken for the real robot, the DwP reductio strictly no longer holds against it; however, this does not help the computationlist as any putative phenomenal states of the real robot have now become tightly bound to properties of the real-world agent/environment interactions and not the mere computations.

  13. Copeland’s argument is detailed, but at heart he follows an extremely simple line of reasoning: consider an idealised analogue computer that can add two reals (a, b) and output one if they are the same, zero otherwise. Clearly either (a) or (b) could be non-computable numbers (in the specific formal sense of non-Turing-computable numbers). Hence clearly, there exists no TM that, for any finite precision (k), can decide the general function F(a = b) (see [67] for detailed discussion of the implications of this result).

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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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    John Mark Bishop

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Bishop, J.M. A Cognitive Computation Fallacy? Cognition, Computations and Panpsychism. Cogn Comput 1, 221–233 (2009). https://doi.org/10.1007/s12559-009-9019-6

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