The Abstraction/Representation Account of Computation and Subjective Experience

Abstract

I examine the abstraction/representation theory of computation put forward by Horsman et al., connecting it to the broader notion of modeling, and in particular, model-based explanation, as considered by Rosen. I argue that the ‘representational entities’ it depends on cannot themselves be computational, and that, in particular, their representational capacities cannot be realized by computational means, and must remain explanatorily opaque to them. I then propose that representation might be realized by subjective experience (qualia), through being the bearer of the structure of abstract objects that are represented.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2

References

  1. Block, N. (1980). Troubles with functionalism. Readings in Philosophy of Psychology, 1, 268–305.

    Google Scholar 

  2. Boolos, G. S., & Jeffrey, R. C. (1989). Computability and logic. Cambridge: Cambridge University Press.

    Google Scholar 

  3. Bringsjord, S., & Zenzen, M. (2003). Superminds: People harness hypercomputation, and more (Vol. 29). Berlin: Springer Science & Business Media.

    Google Scholar 

  4. Carnap, R. (1956). The methodological character of theoretical concepts. In H. Feigl & M. Scriven (Eds.), The foundations of science and the concepts of psychology and psychoanalysis (pp. 38–76). Minneapolis: University of Minnesota Press.

    Google Scholar 

  5. Carruthers, P. (2007). Higher-order theories of consciousness. The Blackwell companion to consciousness (pp. 288–297). Oxford: Blackwell.

    Google Scholar 

  6. Chaitin, G. (2006). The limits of reason. Scientific American, 294(3), 74–81.

    Google Scholar 

  7. Chalmers, D. J. (1994). On implementing a computation. Minds and Machines, 4(4), 391–402.

    Google Scholar 

  8. Chalmers, D. J. (1995). Facing up to the problem of consciousness. Journal of consciousness studies, 2(3), 200–219.

    Google Scholar 

  9. Chalmers, D. J. (1996). The conscious mind: In search of a fundamental theory. Oxford: Oxford University Press.

    Google Scholar 

  10. Church, A. (1932). A set of postulates for the foundation of logic. Annals of Mathematics, 33, 346–366.

    MathSciNet  MATH  Google Scholar 

  11. Clark, A. (2015). Surfing uncertainty: Prediction, action, and the embodied mind. Oxford: Oxford University Press.

    Google Scholar 

  12. Copeland, B. J., & Proudfoot, D. (1999). Alan Turing’s forgotten ideas in computer science. Scientific American, 280(4), 98–103.

    Google Scholar 

  13. Cubitt, T. S., Perez-Garcia, D., & Wolf, M. M. (2015). Undecidability of the spectral gap. Nature, 528(7581), 207.

    Google Scholar 

  14. de Oliveira, G.S. (2018). Representationalism is a dead end. Synthese. https://doi.org/10.1007/s11229-018-01995-9

    Article  Google Scholar 

  15. Demopoulos, W., & Friedman, M. (1985). Bertrand Russell’s the analysis of matter: Its historical context and contemporary interest. Philosophy of Science, 52(4), 621–639.

    Google Scholar 

  16. Dennett, D. C. (1988). Quining qualia. In Bisiach, E. & Marcel, A. (Eds.), Consciousness in modern science. Oxford: Oxford University Press.

    Google Scholar 

  17. Eddington, A. (1928). The nature of the physical world. New York: Macmillan.

    Google Scholar 

  18. Enderton, H. (2001). A mathematical introduction to logic. Amsterdam: Elsevier.

    Google Scholar 

  19. Fodor, J. A. (1975). The language of thought. Harvard: Harvard University Press.

    Google Scholar 

  20. Fuchs, C. A. (2017). On participatory realism. Information and interaction (pp. 113–134). Berlin: Springer.

    Google Scholar 

  21. Gödel, K. (1931). Über formal unentscheidbare Sätze der Principia Mathematica und verwandter Systeme I. Monatshefte für Mathematik und Physik, 38(1), 173–198.

    MathSciNet  MATH  Google Scholar 

  22. Godfrey-Smith, P. (2009). Triviality arguments against functionalism. Philosophical Studies, 145(2), 273–295.

    Google Scholar 

  23. Hameroff, S. R., & Penrose, R. (2017). Consciousness in the universe: An updated review of the “Orch-OR” theory of consciousness. In J. A. Tuszynski, T. E. Feinberg, & R. R. Poznanski (Eds.), A foundational approach, biophysics of consciousness (pp. 517–599). Singapore: World Scientific.

    Google Scholar 

  24. Horsman, C., Stepney, S., Wagner, R. C., & Kendon, V. (2014). When does a physical system compute? Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 470(2169), 20140182.

    MATH  Google Scholar 

  25. Horsman, D. C. (2015). Abstraction/representation theory for heterotic physical computing. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 373(2046), 20140224.

    Google Scholar 

  26. Horsman, D., Kendon, V., Stepney, S., & Young, J. P. W. (2017). Abstraction and representation in living organisms: When does a biological system compute? Representation and reality in humans, other living organisms and intelligent machines (pp. 91–116). Berlin: Springer.

    Google Scholar 

  27. Jackson, F. (1982). Epiphenomenal qualia. The Philosophical Quarterly (1950-), 32(127), 127–136.

    Google Scholar 

  28. James, W. (1884). What is an emotion? Mind, 9(34), 188–205.

    Google Scholar 

  29. Kenny, A. J. (1971). The homunculus fallacy. In M. Grene & I. Prigogine (Eds.), Interpretations of life and mind: Essays around the problem of reduction (pp. 65–74). London: Routledge.

    Google Scholar 

  30. Kim, J. (1987). “Strong” and “Global” supervenience revisited. Philosophy and Phenomenological Research, 48(2), 315–326.

    Google Scholar 

  31. Kleene, S. C. (1943). Recursive predicates and quantifiers. Transactions of the American Mathematical Society, 53(1), 41–73.

    MathSciNet  MATH  Google Scholar 

  32. Kleene, S. C. (1952). Introduction to metamathematics. New York: van Nordstrand.

    Google Scholar 

  33. Klein, C. (2008). Dispositional implementation solves the superfluous structure problem. Synthese, 165(1), 141–153.

    Google Scholar 

  34. Kriegel, U. (2003). The new mysterianism and the thesis of cognitive closure. Acta Analytica, 18(30–31), 177–191.

    Google Scholar 

  35. Kriegel, U. (2009). Subjective consciousness: A self-representational theory. Oxford: Oxford University Press.

    Google Scholar 

  36. Kriegel, U., & Williford, K. (Eds.). (2006). Self-representational approaches to consciousness. Cambridge: MIT Press.

    Google Scholar 

  37. Lange, C. G. (1887). Über Gemütsbewegungen (Org.Om Sindsbevægelser). Leipzig: Thomas Theodor.

    Google Scholar 

  38. Levine, J. (1983). Materialism and qualia: The explanatory gap. Pacific Philosophical Quarterly, 64(4), 354–361.

    Google Scholar 

  39. Lycan, W. G. (1981). Form, function, and feel. The Journal of Philosophy, 78(1), 24–50.

    Google Scholar 

  40. Lycan, W. G. (2015). Representational theories of consciousness. Metaphysics research lab. In E. N. Zalta (Ed.), The stanford encyclopedia of philosophy, summer 2015 ed. Stanford: Stanford University.

    Google Scholar 

  41. Miller, F. (1882). Telegraphic code to insure privacy and secrecy in the transmission of telegrams. New York: CM Cornwell.

    Google Scholar 

  42. Nagel, T. (1974). What is it like to be a bat? The Philosophical Review, 83(4), 435–450.

    Google Scholar 

  43. Newman, M. H. (1928). Mr. Russell’s “Causal Theory of Perception”. Mind, 37(146), 137–148.

    Google Scholar 

  44. Paterek, T., Kofler, J., Prevedel, R., Klimek, P., Aspelmeyer, M., Zeilinger, A., et al. (2010). Logical independence and quantum randomness. New Journal of Physics, 12(1), 013019.

    MathSciNet  MATH  Google Scholar 

  45. Peres, A., & Zurek, W. H. (1982). Is quantum theory universally valid? American Journal of Physics, 50(9), 807–810.

    Google Scholar 

  46. Piccinini, G. (2015). Physical computation: A mechanistic account. Oxford: Oxford University Press.

    Google Scholar 

  47. Putnam, H. (1960). Minds and machines. In S. Hook (Ed.), Dimensions of mind: A symposium (pp. 138–164). New York: Collier.

    Google Scholar 

  48. Putnam, H. (1988). Representation and reality. Cambridge: MIT press.

    Google Scholar 

  49. Rice, H. G. (1953). Classes of recursively enumerable sets and their decision problems. Transactions of the American Mathematical Society, 74(2), 358–366.

    MathSciNet  MATH  Google Scholar 

  50. Robič, B. (2015). The foundations of computability theory. Berlin: Springer.

    Google Scholar 

  51. Rogers, H. (1967). Theory of recursive functions and effective computability (Vol. 5). New York: McGraw-Hill.

    Google Scholar 

  52. Rosen, R. (1991). Life itself: A comprehensive inquiry into the nature, origin, and fabrication of life. New York: Columbia University Press.

    Google Scholar 

  53. Russell, B. (1927). The analysis of matter. London: Routledge.

    Google Scholar 

  54. Seager, W. (2006). The ‘Intrinsic Nature’ argument for panpsychism. Journal of Consciousness Studies, 13(10–11), 129–145.

    Google Scholar 

  55. Seager, W. (2016). Theories of consciousness: an introduction (2nd ed.). Abingdon: Routledge.

    Google Scholar 

  56. Searle, J. R. (1992). The rediscovery of the mind. Cambridge: MIT press.

    Google Scholar 

  57. Shagrir, O. (2006). Why we view the brain as a computer. Synthese, 153(3), 393–416.

    MathSciNet  Google Scholar 

  58. Shagrir, O. (2012). Computation, implementation, cognition. Minds and Machines, 22(2), 137–148.

    Google Scholar 

  59. Shoemaker, S. (1982). The inverted spectrum. The Journal of Philosophy, 79(7), 357–381.

    Google Scholar 

  60. Strawson, G. (2006). Realistic monism: Why physicalism entails panpsychism. Journal of Consciousness Studies, 13(10/11), 3.

    Google Scholar 

  61. Strawson, G. (2019). What does “physical” mean? a prolegomenon to physicalist panpsychism. In W. Seager (Ed.), The Routledge handbook of panpsychism. Abingdon: Routledge.

    Google Scholar 

  62. Szangolies, J. (2015). Von Neumann minds: Intentional automata. Mind Matter, 13(2), 169–191.

    Google Scholar 

  63. Szangolies, J. (2018a). Epistemic horizons and the foundations of quantum mechanics. Foundations of Physics, 48(12), 1669–1697.

    MATH  Google Scholar 

  64. Szangolies, J. (2018b). Von Neumann minds: A toy model of meaning in a natural world. In B. Foster, Z. Merali, & A. Aguirre (Eds.), Wandering towards a goal (pp. 29–39). Berlin: Springer.

    Google Scholar 

  65. Tetens, H. (2013). Wissenschaftstheorie: Eine Einführung, vol 2808. CH Beck.

  66. Turing, A. M. (1937). On computable numbers, with an application to the Entscheidungsproblem. Proceedings of the London Mathematical Society, 2(1), 230–265.

    MathSciNet  MATH  Google Scholar 

  67. von Neumann, J. (1966). The theory of automata: construction, reproduction, homogeneity, original unpublished manuscript, 1952–1953. In A. W. Burke (Ed.), Theory of self-reproducing automata (pp. 91–381). Urbana: University of Illinois Press.

    Google Scholar 

  68. Whitehead, A. N. (1925). Science and the modern world. Cambridge: Cambridge University Press.

    Google Scholar 

  69. Yanofsky, N. S. (2003). A universal approach to self-referential paradoxes, incompleteness and fixed points. Bulletin of Symbolic Logic, 9(3), 362–386.

    MathSciNet  MATH  Google Scholar 

  70. Zwick, M. (1978). Quantum measurement and Gödel’s proof. Speculations in Science and Technology, 1(2), I978.

    Google Scholar 

Download references

Acknowledgements

I warmly thank Peter Hankins and two anonymous referees for comments and criticism on earlier versions of many of the arguments presented here.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Jochen Szangolies.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Szangolies, J. The Abstraction/Representation Account of Computation and Subjective Experience. Minds & Machines 30, 259–299 (2020). https://doi.org/10.1007/s11023-020-09522-x

Download citation

Keywords

  • Computationalism
  • Implementation
  • Mental representation
  • Mental modeling