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Superstition in the Machine

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Book cover Anticipatory Behavior in Adaptive Learning Systems (ABiALS 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4520))

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Abstract

It seems characteristic for humans to detect structural patterns in the world to anticipate future states. Therefore, scientific and common sense cognition could be described as information processing which infers rule-like laws from patterns in data-sets. Since information processing is the domain of computers, artificial cognitive systems are generally designed as pattern discoverers.

This paper questions the validity of the information processing paradigm as an explanation for human cognition and a design principle for artificial cognitive systems. Firstly, it is known from the literature that people suffer from conditions such as information overload, superstition, and mental disorders. Secondly, cognitive limitations such as a small short-term memory, the set-effect, the illusion of explanatory depth, etc. raise doubts as to whether human information processing is able to cope with the enormous complexity of an infinitely rich (amorphous) world.

It is suggested that, under normal conditions, humans construct information rather than process it. The constructed information contains anticipations which need to be met. This can be hardly called information processing, since patterns from the “outside” are not used to produce action but rather to either justify anticipations or restructure the cognitive apparatus.

When it fails, cognition switches to pattern processing, which, given the amorphous nature of the experiential world, is a lost cause if these patterns and inferred rules do not lead to a (partial) reorganisation of internal structures such that constructed anticipations can be met again.

In this scenario, superstition and mental disorders are the result of a profound and/or random restructuring of already existing cognitive components (e.g., action sequences). This means that whenever a genuinely cognitive system is exposed to pattern processing it may start to behave superstitiously. The closer we get to autonomous self-motivated artificial cognitive systems, the bigger the danger becomes of superstitious information processing machines that “blow up” rather than behave usefully and effectively. Therefore, to avoid superstition in cognitive systems they should be designed as information constructing entities.

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References

  1. Angeline, P.J., Pollack, J.B.: Coevolving high-level representations. In: Langton, C. (ed.) Artificial life III, pp. 55–71. Addison-Wesley, Reading (1994)

    Google Scholar 

  2. Arbib, M.: Schema theory. In: Shapiro, S. (ed.) Encyclopedia of artificial intelligence, 2nd edn. vol. 2, pp. 1427–1443. Wiley, New York (1992)

    Google Scholar 

  3. Arthur, W.B.: Inductive reasoning and bounded rationality. American Economic Review 84, 406–411 (1994)

    Google Scholar 

  4. Ashby, W.R.: Design for a brain. Chapman & Hall, London (1952)

    Google Scholar 

  5. Ashby, W.R.: An introduction to cybernetics, 2nd edn. Chapman & Hall, London (1956)

    MATH  Google Scholar 

  6. Bickhard, M.H.: Function, anticipation and representation. In: Dubois, D.M. (ed.): Computing anticipatory systems (CASYS 2000). American Institute of Physics, Melville, pp. 459–469 (2001)

    Google Scholar 

  7. Bridgman, P.W.: The nature of physical theory. John Wiley & Sons, New York (1936)

    Google Scholar 

  8. Brugger, P.: From haunted brain to haunted science: A cognitive neuroscience view of paranormal and pseudoscientific thought. In: Houran, J., Lange, R. (eds.): Hauntings and poltergeists: Multidisciplinary perspective. McFarland, Jefferson, pp. 195–213 (2001)

    Google Scholar 

  9. Cannon, W.B.: The wisdom of the body. Norton, New Yorks (1932)

    Google Scholar 

  10. Carnap, R.: Der logische Aufbau der Welt. Felix Meiner Verlag, Leipzig (1928). English translation: Carnap, R.: The logical structure of the world. Pseudoproblems in philosophy. University of California: Berkeley (1967)

    Google Scholar 

  11. Clancey, W.J.: Review of Rosenfield’s ‘The Invention of Memory’. Artificial Intelligence 50, 241–284 (1991)

    Article  Google Scholar 

  12. Clancey, W.J.: “Situated ” means coordinating without deliberation. McDonnel Foundation Conference, Santa Fe (1992)

    Google Scholar 

  13. Conrad, K.: Die beginnende Schizophrenie. Versuch einer Gestaltanalyse des Wahns. Thieme, Stuttgart (1958)

    Google Scholar 

  14. Dennett, D.C.: Cognitive wheels: The frame problem of AI. In: Hookway, C. (ed.) Minds, machines, and evolution: Philosophical studies, pp. 129–151. Cambridge University Press, London (1984)

    Google Scholar 

  15. Dennett, D.C.: Consciousness explained. Little, Brown & Co, London (1991)

    Google Scholar 

  16. Diettrich, D.: A physical approach to the construction of cognition and to cognitive evolution. Foundations of Science 6, 273–341 (2001)

    Article  MathSciNet  Google Scholar 

  17. Drescher, G.L.: Made-up minds: A constructivist approach to artificial intelligence. MIT Press, Cambridge (1991)

    MATH  Google Scholar 

  18. Duhem, P.: The aim and structure of physical theory (French original published in 1906). Princeton University Press, Princeton (1954)

    MATH  Google Scholar 

  19. Duncker, K.: Zur Psychologie des produktiven Denkens. Springer, Berlin (1935). English translation: Duncker, K.: On problem solving. Psychological Monographs 58, 1–112 (1945)

    Google Scholar 

  20. Einstein, D., Menzies, R.: The presence of magical thinking in obsessive compulsive disorder. Behaviour Research and Therapy 42, 539–549 (2004)

    Article  Google Scholar 

  21. Foerster von, H.: Molecular ethology. An immodest proposal for semantic clarification. In: Ungar, G. (ed.): Molecular mechanisms in memory and learning, pp. 213–248. Plenum Press, New York (1970) Reprinted in Foerster von, H.: Observing systems. Intersystems Publications, Seaside, pp. 149–188 (1982)

    Google Scholar 

  22. Foerster von, H.: Ethics and second-order cybernetics. Cybernetics & Human Knowing 1, 9–19 (1992)

    Google Scholar 

  23. Frost, R., Krause, M., McMahon, M., Peppe, J., Evans, M., McPhee, A., Holden, M.: Compulsivity and superstitiousness. Behaviour Research and Therapy 31, 423–426 (1993)

    Article  Google Scholar 

  24. Gigerenzer, G.: Adaptive thinking. Oxford University Press, Oxford (2000)

    Google Scholar 

  25. Glasersfeld von, E.: Radical constructivism. Falmer Press, London (1995)

    Google Scholar 

  26. Gosselin, F., Schyns, P.G.: Superstitious perceptions reveal properties of internal representations. Psychological Science 14, 505–509 (2003)

    Article  Google Scholar 

  27. Hesslow, G.: Conscious thought as simulation of behaviour and perception. Trends in Cognitive Sciences 6, 242–247 (2002)

    Article  Google Scholar 

  28. Hong, F.T.: Deciphering the enigma of human creativity: Can a digital computer think? IPSP-2003 VIP Forum, October 4-11, 2003, Sveti Stefan, Montenegro (2003)

    Google Scholar 

  29. Hoyningen-Huene, P.: The nature of science. Nature & Resources 35, 4–8 (1999)

    Google Scholar 

  30. Huettel, S.A., Mack, P.B., McCarthy, G.: Perceiving patterns in random series: Dynamic processing of sequence in prefrontal cortex. Nature Neuroscience 5, 485–490 (2002)

    Google Scholar 

  31. Humphrys, M.: Action selection methods using reinforcement learning. PhD Thesis Trinity Hall, Cambridge (1997)

    Google Scholar 

  32. Kant, I.: Kritik der reinen Vernunft. Zweite Ausgabe. Reclam jun, Leipzig, English translation: Critique of pure reason, Second edition.(1781)

    Google Scholar 

  33. Keil, F.C.: Folkscience: Coarse interpretations of a complex reality. Trends in Cognitive Sciences 7, 368–373 (2003)

    Article  Google Scholar 

  34. Kozhamthadam, J.: The discovery of Kepler’s Laws. University of Notre Dame Press, Notre Dame (1994)

    Google Scholar 

  35. Lakatos, I.: Falsification and the methodology of scientific research programmes. In: Lakatos, I., Musgrave, A. (eds.) Criticism and the growth of knowledge, pp. 91–195. Cambridge University Press, London (1970)

    Google Scholar 

  36. Langer, E.J.: The illusion of control. Journal of Personality and Social Psychology 32, 311–328 (1975)

    Article  Google Scholar 

  37. Lindeman, M., Aarnio, K.: Superstitious, magical, and paranormal beliefs: An integrative model. Journal of Research in Personality (in press)

    Google Scholar 

  38. Lorenz, K.Z., Tinbergen, K.: Taxis und Instinkthandlung in der Eirollbewegung der Graugans. Zeitschrift für Tierpsychologie 2, 1–29 (1939)

    Article  Google Scholar 

  39. Lubow, R.E., Gewirtz, J.C.: Latent inhibition in humans: Data, theory, and implications for schizophrenia. Psychological Bulletin 117, 87–103 (1995)

    Article  Google Scholar 

  40. Luchins, A.S.: Mechanization in problem solving. The effect of einstellung. Psychological Monographs 54/248 (1942)

    Google Scholar 

  41. Mach, E.: Knowledge and error. Sketches on the psychology of enquiry. (German original was published in 1905). Reidel, Dordrecht (1976)

    Google Scholar 

  42. Mach, E.: Popular scientific lectures. The Open Court, La Salle (Originally published in 1893) (1986)

    Google Scholar 

  43. Malinowski, B.: Magic, science and religion and other essays. Free Press, Glencoe (Originally published in 1925) (1948)

    Google Scholar 

  44. Maturana, H.R.: Autopoiesis: reproduction, heredity and evolution. In: Zeleny, M. (ed.) Autopoiesis, dissipative structures and spontaneous social orders, pp. 48–80. Westview Press, Boulder (1980)

    Google Scholar 

  45. McAllister, J.W.: Phenomena and patterns in data sets. Erkenntnis 47, 217–228 (1997)

    Google Scholar 

  46. McAllister, J.W.: The amorphousness of the world. In: Cachro, J., Kijania-Placek, K. (eds.): IUHPS 11th International Congress of Logic, Methodology and Philosophy of Science. Jagiellonian University, Cracow, 189 (1999)

    Google Scholar 

  47. McAllister, J.W.: Algorithmic randomness in empirical data. Studies in the History and Philosophy of Science 34, 633–646 (2003)

    Article  MathSciNet  Google Scholar 

  48. Neisser, U.: Cognitive psychology. Meredith, New York (1967)

    Google Scholar 

  49. Neisser, U.: Cognition and reality. W. H. Freeman, San Francisco (1976)

    Google Scholar 

  50. O’Regan, J.K.: Solving the “ real ” mysteries of visual perception: The world as an outside memory. Canadian Journal of Psychology 46, 461–488 (1992)

    Google Scholar 

  51. Oyama, S.: The ontogeny of information: Developmental systems and evolution (Republished in 2000). Cambridge University Press, Cambridge (1985)

    Google Scholar 

  52. Pörksen, B.: The certainty of uncertainty (German original appeared in 2001). Imprint, Exeter (2004).

    Google Scholar 

  53. Porr, B., Wörgötter, F.: Inside embodiment. What means embodiment to radical constructivists? Kybernetes 34, 105–117 (2005)

    Article  Google Scholar 

  54. Powers, W.T.: Behavior. The control of perception. Aldine de Gruyter, New York (1973)

    Google Scholar 

  55. Quine, W.V.: Word and object. MIT Press, Cambridge (1960)

    MATH  Google Scholar 

  56. Riegler, A.: When is a cognitive system embodied? Cognitive Systems Research 3, 339–348 (2002)

    Article  Google Scholar 

  57. Rudski, J.M.: The illusion of control, superstitious belief, and optimism. Current Psychology 22, 306–315 (2004)

    Article  Google Scholar 

  58. Sacks, O.: An anthropologist on Mars. Alfred A. Knopf, New York (1995)

    Google Scholar 

  59. Simon, H.A.: The architecture of complexity. In: Simon, H.A.: The sciences of the artificial, pp. 192–229. MIT Press, Cambridge (1969)

    Google Scholar 

  60. Simon, H.A.: Does scientific discovery have a logic? Philosophy of Science 40, 471–480 (1973)

    Article  Google Scholar 

  61. Skinner, B.F.: ‘Superstition’ in the pigeon. Journal of Experimental Psychology 38, 168–172 (1948)

    Article  Google Scholar 

  62. Spelke, E.S.: Core knowledge. American Psychologist 55, 1233–1243 (2000)

    Google Scholar 

  63. Tsang, E.W.K.: Superstition and decision-making. Contradiction or complement? Academy of Management Executive 18, 92–104 (2004)

    Google Scholar 

  64. Tyrrell, T.: Computational mechanisms for action selection. PhD thesis, University of Edinburgh, Centre for Cognitive Science (1993)

    Google Scholar 

  65. Vyse, S.A.: Believing in magic. In: The psychology of superstition, Oxford University Press, New York (1997)

    Google Scholar 

  66. Zebb, B.J., Moore, M.C.: Superstitiousness and perceived anxiety control as predictors of psychological distress. Anxiety Disorders 17, 115–130 (2003)

    Article  Google Scholar 

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Martin V. Butz Olivier Sigaud Giovanni Pezzulo Gianluca Baldassarre

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Riegler, A. (2007). Superstition in the Machine. In: Butz, M.V., Sigaud, O., Pezzulo, G., Baldassarre, G. (eds) Anticipatory Behavior in Adaptive Learning Systems. ABiALS 2006. Lecture Notes in Computer Science(), vol 4520. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74262-3_4

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  • DOI: https://doi.org/10.1007/978-3-540-74262-3_4

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