PL: ZARZUTY WOBEC KOMPUTACJONIZMU — PRZEGLĄD
Źódło/source:	Roczniki Filozoficzne, 66 (2018), nr 3
Strony/pages:	35-75

 

http://dx.doi.org/10.18290/rf.2018.66.3-3

 

Streszczenie

W artykule Autor przyjrzał się typowym zastrzeżeniom przeciwko twierdzeniu, że mózgi to kom­putery, a ściślej — mechanizmy przetwarzania informacji. Pokazując, że praktycznie wszyst­kie popularne obiekcje są oparte na nieżyczliwych (lub po prostu niepoprawnych) interpretacjach tego twierdzenia, uznaje, że twierdzenie to prawdopodobnie będzie prawdziwe, istotne dla współ­czesnej (neuro)kognitywistyki i nietrywialne.

 

 

Summary

In this paper, the Author reviewed the typical objections against the claim that brains are com­puters, or, to be more precise, information-processing mechanisms. By showing that practi­cally all the popular objections are based on uncharitable (or simply incorrect) interpretations of the claim, he argues that the claim is likely to be true, relevant to contemporary cognitive (neuro) science, and non-trivial.

 

  

Słowa kluczowe: komputacjonizm; komputacjonalna teoria umysłu; reprezentacja; komputacja; mo­de­lowanie.

Key words: computationalism; computational theory of mind; representation; computation; mo­deling.

 

 

Bibliografia/References:

 

1. Akagi, Mikio. 2017 “Rethinking the Problem of Cognition.” Synthese, April 9, 2017, 1–24. DOI: https://doi.org/10.1007/s11229-017-1383-2.

2. Baars, Bernard J. 1988. A Cognitive Theory of Consciousness. Cambridge, New York: Cam­bridge University Press.

3. Bar-Hillel, Yehoshua. 1964. “A Demonstration of the Nonfeasibility of Fully Automatic High Quality Translation.” In Language and Information, 174–79. Reading, Mass.: Addison-Wesley.

4. Barrett, Louise. 2016. “Why Brains Are Not Computers, Why Behaviorism Is Not Satanism, and Why Dolphins Are Not Aquatic Apes.” The Behavior Analyst vol 39, issue 1: 9–23. DOI: https://doi.org/10.1007/s40614-015-0047-0.

5. Barrett, Louise, Thomas V. Pollet, & Gert Stulp. 2014. “From Computers to Cultivation: Recon­ceptualizing Evolutionary Psychology.” Frontiers in Psychology 5 (January 2014): 867–867. DOI: https://doi.org/10.3389/fpsyg.2014.00867.

6. Bickhard, Mark H. 2009. “The Interactivist Model.” Synthese vol. 166, no. 3: 547–91. DOI: https://doi.org/ 10.1007/s11229-008-9375-x.

7. Bickhard, Mark H., & Loren Terveen. 1995. Foundational Issues in Artificial Intelligence and Cognitive Science: Impasse and Solution. Amsterdam, Lausane, New York, Oxford, Shan­non, Tokyo: North-Holland.

8. Block, Ned. “The Mind as the Software of the Brain.” In An Invitation to Cognitive Science, edited by Daniel N. Osherson, Lila Gleitman, & Stephen Kosslyn. Cambridge, Mass.: MIT Press, 1995.

9. Chalmers, David J. 2011. “A Computational Foundation for the Study of Cognition.” Journal of Cognitive Science, no. 12: 325–59.

10. Chalmers, David J. 1996. The Conscious Mind: In Search of a Fundamental Theory. New York: Oxford University Press.

11. Chemero, Anthony. 2003 “Information for Perception and Information Processing.” Minds and Machines vol. 13 577–88.

12. Chrisley, Ronald L. 1994. “Why Everything Doesn’t Realize Every Computation.” Minds and Machines vol. 4, no. 4: 403–20. DOI: https://doi.org/10.1007/BF00974167.

13. Cleeremans, Axel. 2005. “Computational Correlates of Consciousness.” Progress in Brain Research vol. 150: 81–98. DOI: https://doi.org/10.1016/S0079-6123(05)50007-4.

14. Collier, John D. 1999. “Causation Is the Transfer of Information.” In Howard Sankey (ed.). Causation, Natural Laws and Explanation, 279–331. Dordrecht: Kluwer.

15. Copeland, B. Jack. 1996. “What Is Computation?”. Synthese vol. 108, no. 3: 335–59.

16. Cummins, Robert, & Martin Roth. 2012. “Meaning and Content in Cognitive Science.” In Ri­chard Schantz (ed.). Prospects for Meaning, 365–82. Berlin & New York: de Gruyter.

17. Daugman, John. 1990. “Brain Metaphor and Brain Theory.” In Eric L. Schwartz (ed.). Com­putational Neuroscience, 9–18. Cambridge, Mass: MIT Press, 1990.

18. Deacon, Terrence W. 2012. Incomplete Nature: How Mind Emerged from Matter. New York: W.W. Norton & Co.

19. Dennett, Daniel C. 2017. From Bacteria to Bach and Back: The Evolution of Minds. London: Allen Lane.

20. Dennett, Daniel C. 2005. Sweet Dreams. Philosophical Obstacles to a Science of Con­scious­ness. Cambridge, Mass.: MIT Press.

21. Dresner, Eli. 2010. “Measurement-Theoretic Representation and Computation-Theoretic Reali­zation.” The Journal of Philosophy vol. 107, no. 6: 275–92.

22. Dretske, Fred I. 1986. “Misrepresentation.” In Radu Bogdan (ed). Belief: Form, Content, and Function, 17–37. Oxford: Clarendon Press.

23. Dreyfus, Hubert. 1972. What Computers Can’t Do: A Critique of Artificial Reason. New York: Harper & Row Publishers.

24. Dreyfus, Hubert. 1979. What Computers Still Can’t Do: A Critique of Artificial Reason. Cam­bridge Mass.: MIT Press.

25. Edelman, Gerald M. 1992. Bright Air, Brilliant Fire: On the Matter of the Mind. New York, N.Y.: BasicBooks.

26. Egan, Frances. 1995. “Computation and Content.” The Philosophical Review vol. 104, no. 2: 181–181. DOI: https://doi.org/10.2307/2185977.

27. Ekman, Paul. 2003. Emotions Revealed: Recognizing Faces and Feelings to Improve Com­mu­nication and Emotional Life. New York: Times Books.

28. Epstein, Robert. 2016. “The Empty Brain.” Aeon, May 18, 2016. https://aeon.co/essays/your-brain-does-not-process-information-and-it-is-not-a-computer.

29. Fresco, Nir. 2010. “Explaining Computation Without Semantics: Keeping It Simple.” Minds and Machines vol. 20, no. 2: 165–81. DOI: https://doi.org/10.1007/s11023-010-9199-6.

30. Fresco, Nir. 2014. Physical Computation and Cognitive Science. (Studies in Applied Philo­sophy, Epistemology and Rational Ethics). Berlin, Heidelberg: Springer-Verlag.

31. Fresco, Nir, & Marty J. Wolf. 2013. “The Instructional Information Processing Account of Digital Computation.” Synthese vol. 191, no. 7: 1469–92. DOI: https://doi.org/10.1007/ s11229-013-0338-5.

32. Friston, Karl. 2012, “A Free Energy Principle for Biological Systems.” Entropy (Basel, Switzerland) vol. 14, no. 11: 2100–2121. DOI: https://doi.org/10.3390/e14112100.

33. Froese, Tom, & John Robert Stewart. 2010. “Life After Ashby: Ultrastability and the Auto­poietic Foundations of Biological Autonomy.” Cybernetics & Human Knowing vol. 17, no. 4: 7–50.

34. Gallistel, C.R., & Adam Philip King. 2010. Memory and the Computational Brain. Chichester: Wiley-Blackwell.

35. Gibson, James J. 1986. The Ecological Approach to Visual Perception. Hove: Psychology Press.

36. Goldinger, Stephen D., Megan H. Papesh, Anthony S. Barnhart, Whitney A. Hansen, & Michael C. Hout. 2016. “The Poverty of Embodied Cognition.” Psychonomic Bulletin & Review vol. 23, no. 4: 959–78. DOI: https://doi.org/10.3758/s13423-015-0860-1.

37. Hameroff, Stuart R. 2007. “The Brain Is Both Neurocomputer and Quantum Computer.” Cog­nitive Science vol. 31, no. 6: 1035–45.

38. Harnad, Stevan. 1990. “The Symbol Grounding Problem.” Physica D 42: 335–46.

39. Haugeland, John. 1985 Artificial Intelligence: The Very Idea. Cambridge, Mass.: MIT Press.

40. Krajewski, Stanisław. 2007. “On Gödel’s Theorem and Mechanism: Inconsistency or Unsound­ness Is Unavoidable in Any Attempt to ‘Out-Gödel’ the Mechanist.” Fundamenta Infor­maticae vol. 81, no. 1–3: 173–81.

41. Lakoff, George. 1987. Women, Fire, and Dangerous Things: What Categories Reveal about the Mind. Chicago: University of Chicago Press.

42. Leibniz, Gottfried Wilhelm. 1991. The Monadology. Translated by Robert Latta. Raleigh, NC; Boulder, Colo.: Alex Catalogue; NetLibrary.

43. Lucas, J.R. 1961. “Minds, Machines and Gödel.” Philosophy vol. 36, no. 137: 219–27.

44. Lupyan, Gary. 2013. “The Difficulties of Executing Simple Algorithms: Why Brains Make Mistakes Computers Don’t.” Cognition vol. 129, no. 3: 615–36. DOI:  https://doi.org/ 10.1016/ j.cognition.2013.08.015.

45. Lurija, Aleksandr Romanovic̆. 2002. The Mind of a Mnemonist: A Little Book about a Vast Memory. Cambridge, Mass.: Harvard University Press.

46. MacKay, Donald MacCrimmon. 1969. Information, Mechanism and Meaning. Cambridge: MIT Press.

47. Marr, David. 1982. Vision. A Computational Investigation into the Human Representation and Processing of Visual Information. New York: W.H. Freeman and Company.

48. McDermott, Drew V. 2001. Mind and Mechanism. Cambridge, Mass.: MIT Press.

    Miłkowski, Marcin. 2007. “Is Computationalism Trivial?” In Gordana Dodig Crnkovic & Susan Stuart (eds.), Computation, Information, Cog­nition — The Nexus and the Liminal, 236–46. Newcastle: Cambridge Scholars Press. http://marcinmilkowski.pl/downloads/is-computa­tiona­lism- trivial.pdf.

49. Miłkowski, Marcin. 2011. “Jak udawać dualistę, wprowadzając epicykle do funkcjonalizmu.” Przegląd Filo­zoficzny – Nowa Seria, no. 1 (77): 27–45.

50. Miłkowski, Marcin. 2012. “Limits of Computational Explanation of Cognition.” In Vincent C. Müller, Philosophy and Theory of Artificial Intelligence, 69–84. Berlin, Heidelberg: Springer. http://www.springerlink.com/content/k6w34j70459wv782/.

51. Miłkowski, Marcin. 2013. Explaining the Computational Mind. Cambridge, Mass.: MIT Press.

52. Miłkowski, Marcin. 2014. “Computational Mechanisms and Models of Computation.” Philo­sophia Scientiae vol. 18, no. 18–3: 215–28. DOI: https://doi.org/10.4000/ philosophiascientiae. 1019.

53. Miłkowski, Marcin. 2017. “Situatedness and Embodiment of Computational Systems.” Entropy 19, no. 4 (April 7, 2017): 162. https://doi.org/10.3390/e19040162.

54. Millikan, Ruth Garrett. 1984. Language, Thought, and Other Biological Categories: New Foun­da­tions for Realism. Cambridge, Mass.: MIT Press.

55. Müller, Vincent C. (2014). “Pancomputationalism: Theory or metaphor?” In Ruth Hagen­gruber & Uwe V. Riss (eds.). The relevance of philosophy for information science (213–222). London, New York: Routledge.

56. Nagy, Naya, & Selim Akl. 2011. “Computations with Uncertain Time Constraints: Effects on Parallelism and Universality.” In Cristian Calude, Jarkko Kari, Ion Petre, & Grzegorz Rozenberg (eds.). Unconventional Computation, 6714:152–63. (Lecture Notes in Com­puter Science). Berlin, Heidelberg: Springer. DOI: http://dx.doi.org/10.1007/978-3-642-21341-0_19.

57. Newell, Allen. 1980. “Physical Symbol Systems.” Cognitive Science: A Multidisciplinary Jour­nal vol. 4, no. 2: 135–83. DOI: https://doi.org/10.1207/s15516709cog0402_2.

58. Newell, Allen, & Herbert A. Simon. 1972. Human Problem Solving. Englewood Cliffs, NJ: Prentice-Hall.

59. Nowakowski, Przemysław Robert. 2017. “Bodily Processing: The Role of Morphological Com­putation.” Entropy vol. 19, no. 7: 295. DOI: https://doi.org/10.3390/e19070295.

60. Penrose, Roger. 1989. The Emperor’s New Mind. London: Oxford University Press.

61. Piccinini, Gualtiero. 2008. “Computation without Representation.” Philosophical Studies vol. 137, no. 2: 205–41. DOI: https://doi.org/10.1007/s11098-005-5385-4.

62. Piccinini, Gualtiero. 2010. “The Mind as Neural Software? Understanding Functionalism, Com­putationalism, and Computational Functionalism.” Philosophy and Phenomenological Re­search vol. 81, no. 2: 269–311. DOI: https://doi.org/10.1111/j.1933-1592.2010.00356.x.

63. Piccinini, Gualtiero. 2015. Physical Computation: A Mechanistic Account. Oxford: Oxford Uni­versity Press.

64. Piccinini, Gualtiero, & Sonya Bahar. 2013. “Neural Computation and the Computational Theo­ry of Cognition.” Cognitive Science vol. 37, no. 3: 453–88. DOI: https://doi.org/10.1111/ cogs.12012.

65. Preston, John, & Mark Bishop. 2002. Views into the Chinese Room: New Essays on Searle and Artificial Intelligence. Oxford; New York: Clarendon Press.

66. Putnam, Hilary. 1960. “Minds and Machines.” In Sidney Hook (ed.). Dimensions of Mind. New York University Press.

67. Putnam, Hilary. 1991. Representation and Reality. Cambridge, Mass.: The MIT Press, 1991.

68. Pylyshyn, Zenon W. 1984. Computation and Cognition: Toward a Foundation for Cognitive Science. Cambridge, Mass.: MIT Press.

69. Rosenblatt, Frank. 1958 “The Perceptron: A Probabilistic Model for Information Storage and Orga­nization in the Brain.” Psychological Review 65, no. 6: 386–408. DOI: https://doi.org/ 10.1037/h0042519.

70. Rosenthal, David. 2005. Consciousness and Mind. Oxford, New York: Oxford University Press.

71. Scheutz, Matthias. 1996. “When Physical Systems Realize Functions….” Minds and Machines vol. 9, no. 2: 1–34. DOI: https://doi.org/10.1023/A:1008364332419.

72. Searle, John R. 1980. “Minds, Brains, and Programs.” Behavioral and Brain Sciences 3, no. 03 (February 1980): 1–19. https://doi.org/10.1017/S0140525X00005756.

73. Searle, John R. 1990. “Is the Brain’s Mind a Computer Program?”. Scientific American, Janua­ry: 26–31.

74. Searle, John R. 1992. The Rediscovery of the Mind. Cambridge, Mass.: MIT Press, 1992.

75. Shagrir, Oron. 2010a. “Brains as Analog-Model Computers.” Studies In History and Philosophy of Science Part A vol. 41, no. 3: 271–79. DOI: https://doi.org/10.1016/j.shpsa.2010.07.007.

76. Shagrir, Oron. 2011. “Towards a Modeling View of Computing.” In G. Dodig-Crnkovic & M. Bur­gin (eds.). Information and Computation (381–391). Singapore: World Scientific Pub­lishing. DOI:10.1142/9789814295482_0014.

77. Shanahan, Murray. 1997. Solving the Frame Problem: A Mathematical Investigation of the Common Sense Law of Inertia. Cambridge, Mass.: MIT Press.

78. Siegelmann, Hava T., & Eduardo D. Sontag. 1994. “Analog Computation via Neural Net­works.” Theoretical Computer Science vol. 131, no. 2: 331–60. DOI: https://doi.org/ 10.1016/ 0304-3975(94)90178-3.

79. Thompson, Evan. 2007. Mind in Life: Biology, Phenomenology, and the Sciences of Mind. Cambridge, Mass.: Harvard University Press.

80. Tononi, Giulio. 2004. “An Information Integration Theory of Consciousness.” BMC Neuro­science vol. 5, no. 1. https://doi.org/10.1186/1471-2202-5-42.

81. Weizenbaum, Joseph. 1976. Computer Power and Human Reason: From Judgment to Calcu­lation. San Francisco: W.H. Freeman, 1976.

82. Wheeler, Michael. 2005. Reconstructing the Cognitive World. Cambridge, Mass.: MIT Press.

83. Zauner, Klaus-Peter, & Michael Conrad. 1996. “Parallel Computing with DNA: Toward the Anti-Universal Machine.” In Hans-Michael Voigt, Werner Ebeling, Ingo Rechenberg, & Hans-Paul Schwefel (eds.). Parallel Problem Solving from Nature – PPSN IV, 1141:696–705. (Lecture Notes in Computer Science). Berlin, Heidelberg: Springer. DOI: http://dx.doi.org/10.1007/3-540-61723-X_1033.

Informacja o autorze/Information about Author:

Dr hab. Marcin Miłkowski—Department of Logic and Cogni­tive Science at the Institute of Philosophy and Socio­logy of the Polish Academy of Sciences; address for correspondence: ul. Nowy Świat 72, 00‑330 Warszawa; e-mail: mmilkows@ifispan.waw.pl

 

 

Cytowanie/Citation information:

Miłkowski, Marcin. 2018. Objections to Computationalism: A Survey. "Roczniki Filozoficzne" 66, 3: 35-75, DOI: 10.18290/rf.2018.66.3-3.