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Machine Mentality and the Nature of the Ground Relation

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Abstract

John Searle distinguished between weak and strong artificial intelligence (AI). This essay discusses a third alternative, mild AI, according to which a machine may be capable of possessing a species of mentality. Using James Fetzer's conception of minds as semiotic systems, the possibility of what might be called ``mild AI'' receives consideration. Fetzer argues against strong AI by contending that digital machines lack the ground relationship required of semiotic systems. In this essay, the implementational nature of semiotic processes posited by Charles S. Peirce's triadic sign relation is re-examined in terms of the underlying dispositional processes and the ontological levels they would span in an inanimate machine. This suggests that, if non-human mentality can be replicated rather than merely simulated in a digital machine, the direction to pursue appears to be that of mild AI.

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References

  • Baas, N.A. (1994), 'Emergence, hierarchies, and hyperstructures', in C.G. Langton, ed., Artificial Life, Vol. III. Addison-Wesley, pp. 515–537.

  • Baas, N.A. (1996), 'A framework for higher order cognition and consciousness', in S.R. Hameroff, A.W. Kaszniak and A.C. Scott, eds. Toward a science of consciousness. MIT Press, pp. 633–648.

  • Chandler, D. (1995), The act of writing: a media theory approach. Aberystwyth, University of Wales.

    Google Scholar 

  • Cohen, B., Hardwood, W.T. and Jackson, M.I. (1986), The specification of complex system. Addison-Wesley.

  • Copeland, B.J. (1993), Artificial intelligence, a philosophical introduction. Blackwell.

  • DARPA, (1988) DARPA neural network study. AFCEA International Press.

  • Dennett, D.C. (1978), Brainstorms: philosophical essays on mind and psychology. Bradford Books, Harvester Press.

  • Dreyfus, G., Guyon, I., Nadal, J.P. and Personnaz, L. (1988), 'Storage and retrieval of complex sequences in neural networks', Physical Review A 38(12), pp. 6365–6372.

    Google Scholar 

  • von Eckardt, B. (1993), What is cognitive science? Bradford Books, MIT Press.

  • Eco, U. (1976), A theory of semiotics. Indiana University Press.

  • Emmeche, C., Koppe, S. and Stjernfelt, F. (1997), 'Explaining emergence: towards an ontology of levels', Journal for General Philosophy of Science 28, pp. 83–119.

    Google Scholar 

  • Fetzer, J.H. (1977), 'A world of dispositions', Synthese 34, pp. 397–421.

    Google Scholar 

  • Fetzer, J.H. (1981), Scientific knowledge. Dordrecht, Holland: D. Reidel.

    Google Scholar 

  • Fetzer, J.H. (1986), 'Methodological individualisn', Synthese 68, pp. 99–128.

    Google Scholar 

  • Fetzer, J.H. (1990), Artificial intelligence: its scope and limits. Kluwer Academic Publishers.

  • Fetzer, J.H. (1991), 'Primitive concepts: habits, conventions, and laws', J.H. Fetzer, D. Shatz and G. Schlesinger, eds. Definitions and Definability: Philosophical Perspectives, pp. 51–68.

  • Fetzer, J.H. (1993), Philosophy of science. Paragon House.

  • Fetzer, J.H. (1996), Philosophy and cognitive science. Paragon House.

  • Fetzer, J.H. (1998), 'People are not computers: (most) thought processes are not computational procedures', Journal of Experimental & Theoretical Artificial Intelligence 10, pp. 371–391.

    Google Scholar 

  • Fodor, J.A. (1990), A theory of content and other essays. MIT Press.

  • Fujiwara, S., Okajima, K. and Tanaka, S. (1987), 'A Heteroassociative memory network with feedback connection', IEEE International Conference on Neural Networks, Vol. II, pp. 711–718.

    Google Scholar 

  • Hartshorne, C., Weiss, P. and Burks, A. (1958), Collected papers of Charles Sanders Peirce. Eds. Harvard University Press.

  • Hausman, C.R. (1993), Charles S. Peirce's evolutionary philosophy. Cambridge University Press.

  • Hodges, W. (1993), Model theory. Cambridge University Press.

  • Hopfield, J.J. (1982), 'Neural networks and physical systems with emergent collective computational abilities', Proceedings National Academ Science USA, Biophysics 79, pp. 2554–2558.

    Google Scholar 

  • Kosko, B. (1987), 'Adaptive bi-directional associative memories', Applied Optics 26(23), pp. 4947–4960.

    Google Scholar 

  • Kuipers, B. (1986). 'Qualitative simulation', Artificial Intelligence 29, pp. 289–338.

    Google Scholar 

  • Machover, M. (1996), Set theory, logic and their limitations. Cambridge University Press.

  • Mellor, D.H. (1993), 'Supervenience? No chance! Reply to Menuge', Analysis 53(4), pp. 236–239.

    Google Scholar 

  • Moore. G. (1965), Moore's Law. See www.intel.com/intel/museum.

  • Moravec, H. (1999) Robot: mere machine to transcendent mind. Oxford University Press.

  • Morris, C.W. (1938), Foundations of the theory of signs. Chicago University Press.

  • Nanopoulos, D.V. (1995), 'Theory of brain function, quantum mechanics and superstrings', CERNTH/ 95-128. nanopoud@cernvm.cern.ch.

  • Newell, A. and Simon, H.A. (1976), 'Computer science as empirical inquiry: Symbols and search', Communications of the ACM 3, pp. 205–211.

    Google Scholar 

  • Newell, A. (1982), 'The knowledge level', Artificial Intelligence 18, pp. 87–127.

    Google Scholar 

  • Norton A. (1995), 'Dynamics: an introduction', in R.F. Port and T. van Gelder, eds., Mind as Motion, MIT Press, pp. 45–68.

  • Rapaport, W.J. (1998), 'How minds can be computational systems', Journal of Experimental and Theoretical AI 10, pp. 403–419.

    Google Scholar 

  • Rey, G. (1997), Contemporary philosophy of mind. Blackwell.

  • Savage, J.E. (1998), Models of computation. Addison-Wesley.

  • Searle, J.R. (1984), Minds, brains and science: the 1984 Reith lectures. BBC publication.

  • Smullyan, R.M (1994), Diagonalization and self-reference. Oxford Logic Guides, Clarendon Press. No. 27.

  • Turing, A.M. (1950), 'Computing machinery and intelligence', Mind 59, pp. 422–460.

    Google Scholar 

  • Whobrey, D.J.R. (1999), 'Aspects of qualitative consciousness: a computer science perspective', PhD Thesis. Department of Computer Science. City University, London. Online version at: www.mildai.org.

    Google Scholar 

  • Wood, D. (1987), Theory of computation. Harper and Row.

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Whobrey, D. Machine Mentality and the Nature of the Ground Relation. Minds and Machines 11, 307–346 (2001). https://doi.org/10.1023/A:1017521226571

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