Turing Test Considered Mostly Harmless

Abstract

Turing’s landmark paper on computing machinery and intelligence is multifaceted and has an underemphasized ethical dimension. Turing’s notion of “intelligence” and “thinking” was far more encompassing than the common anthropocentric view may suggest. We discuss a number of open and underrated problems that the common interpretation of the Turing test as a test of machine intelligence entails. We suggest that a more meaningful question than “Can machines think?” is whether modern computing machinery can amplify human intelligence. We cite examples ranging from traditional silicon-based environments to carbon-based, living organisms in order to illustrate that this kind of intelligence amplification is indeed happening today. We conclude that in its interpretation as a test of machine intelligence, the Turing test may indeed be harmful for artificial intelligence (AI); in its wider interpretation, however, it remains an inspiring source for philosophy and AI alike.

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References

  1. 1.

    Abramson D.: “Turing’s responses to two objections,”. Minds & Machines 18, 147–167 (2008)

    Article  Google Scholar 

  2. 2.

    Aono M., Hara M., Aihara K., Munakata T.: “Amoeba-based emergent computing: Combinatorial optimization and autonomous meta-problem solving,”. International Journal of Unconventional Computing 6, 89–108 (2010)

    Google Scholar 

  3. 3.

    Beckmann, B. E. and McKinley, P. K., “Evolving quorum sensing in digital organisms,” Proc. of the ACM Genetic and Evolutionary Computation Conference, 2009.

  4. 4.

    Berrar, D., “Revisiting the Turing test from a statistical angle,” International Symposium on Soft Computing, Yokohama, Japan, pp. 1–4, 2012

  5. 5.

    Berrar D., Schuster A.: “The omnipresent computing menace to information society,”. Journal of Advanced Computational Intelligence and Intelligent Informatics 15(7), 786–792 (2011)

    Google Scholar 

  6. 6.

    Berrar, D., Sato, N. and Schuster, A., “Quo vadis, artificial intelligence?” Advances in Artificial Intelligence, Article ID 629869, pp. 3–12, 2010.

  7. 7.

    Block N.: “Psychologism and behaviorism,”. Philosophical Review 1, 5–43 (1981)

    MathSciNet  Article  Google Scholar 

  8. 8.

    Block, N., “The mind as the software of the brain,” in An Invitation to Cognitive Science (Osherson, D. N., Gleitman, L., Kosslyn, S. M., Smith, S. and Sternberg, S., eds.), pp. 377–425, MIT Press, 1995.

  9. 9.

    Boden M.: The Creative Mind: Myths and Mechanisms. Weidenfeld and Nicholson, London (1990)

    Google Scholar 

  10. 10.

    Boden M.: “The Turing and artistic creativity,”. Kybernetes 39(3), 409–413 (2010)

    Article  Google Scholar 

  11. 11.

    Bringsjord S., Bello P., Ferrucci D.: “Creativity, the Turing test, and the (better) Lovelace test,”. Minds & Machines 11, 3–27 (2001)

    Article  MATH  Google Scholar 

  12. 12.

    Chomsky, N., “Turing on the imitation game,” in Parsing the Turing Test: Philosophical and Methodological Issues in the Quest for the Thinking Computer (Epstein, R., Roberts, G. and Beber, G. eds.), pp. 103–106, Springer, 2008.

  13. 13.

    Cohen P.R.: “If not Turing’s test, then what?,”. AI Magazine 26(4), 61–67 (2006)

    Google Scholar 

  14. 14.

    Copeland J.: “The Turing test,”. Minds & Machines 10, 519–539 (2000)

    Article  Google Scholar 

  15. 15.

    Copeland, J. and Proudfoot, D., “Turing’s test - a philosophical and historical guide,” in Parsing the Turing Test: Philosophical and Methodological Issues in the Quest for the Thinking Computer (Epstein, R., Roberts, G. and Beber, G. eds.), pp. 119–138, Springer, 2008.

  16. 16.

    Cowen, T. and Dawson, M., “What does the Turing test really mean? And how many human beings (including Turing) could pass?,” George Mason University, available at http://www.gmu.edu/centers/publicchoice/facultypages/Tyler/turingfinal.pdf, accessed 20 June 2013, 2009.

  17. 17.

    Cronin L., Krasnogor N., Davis B. G., Alexander C., Robertson N., Steinke J. H. G., Schroeder S. L. M., Khlobystov A. N., Cooper G., Gardner P. M., Siepmann P., Whitaker B. J., Marsh D.: “The imitation game - a computational chemical approach to recognizing life,”. Nature Biotechnology 24(10), 1203–1206 (2006)

    Article  Google Scholar 

  18. 18.

    French R.: “Subcognition and the limits of the Turing test,”. Mind 99, 53–65 (1990)

    MathSciNet  Article  Google Scholar 

  19. 19.

    French R.: “Dusting off the Turing test,”. Science 336, 164–165 (2012)

    Article  Google Scholar 

  20. 20.

    Harel D.: “A Turing-like test for biological modeling,”. Nature Biotechnology 23(4), 495–496 (2005)

    Article  Google Scholar 

  21. 21.

    Hayes, P. and Ford, K., “Turing test considered harmful,” Proc. of the 14th International Joint Conference on Artificial Intelligence, pp. 972–977, 1995.

  22. 22.

    Hodges, A., “Alan Turing and the Turing test,” in Parsing the Turing Test: Philosophical and Methodological Issues in the Quest for the Thinking Computer (Epstein, R., Roberts, G. and Beber, G. eds.), pp. 13–22, Springer, 2008.

  23. 23.

    Hodges A.: “Beyond Turing’s machines,”. Science 336, 163–164 (2012)

    Article  Google Scholar 

  24. 24.

    Kim S.J., Aono M., Hara M.: “Tug-of-war model for multi-armed bandit problem,”. Proc. of Unconventional Computing, Springer Lecture Notes in Computer Science, 6079, 69–80 (2010)

    Article  Google Scholar 

  25. 25.

    Koestler A.: The Act of Creation. Hutchinson, London (1964)

    Google Scholar 

  26. 26.

    Kryssanov V. V., Tamaki H., Kitamura S.: “Understanding design fundamentals: how synthesis and analysis drive creativity, resulting in emergence,”. Artificial Intelligence in Engineering 15, 153–169 (2001)

    Article  Google Scholar 

  27. 27.

    Latty T., Beekman M.: “Speed-accuracy trade-offs during foraging decisions in the acellular slime mould Physarum polycephalum,”. Proc. of the Royal Society B: Biological Sciences 278(1705), 539–545 (2010)

    Article  Google Scholar 

  28. 28.

    Martin, R. M., Philosophical Conversations, Broadview Press Ltd., 2008.

  29. 29.

    Mednick S. A.: “The associative basis of the creative process,”. Psychological Review 69(3), 220–232 (1962)

    Article  Google Scholar 

  30. 30.

    Miller M. B., Bassler B. L.: “Quorum sensing in bacteria,”. Annual Reviews in Microbiology 55, 165–199 (2005)

    Article  Google Scholar 

  31. 31.

    Nakagaki, T., Yamada, H. and Tóth, A., “Maze-solving by an amoeboid organism,” Nature, 407 (6803), 470, 2000.

  32. 32.

    Nakagaki T., Kobayashi R., Nishiura Y., Ueda T.: “Obtaining multiple separate food sources: behavioural intelligence in the Physarum plasmodium,”. Proc. of the Royal Society London, Series B 271, 2305–2310 (2004)

    Article  Google Scholar 

  33. 33.

    R Development Core Team, “R: A Language and Environment for Statistical Computing,” R Foundation for Statistical Computing, Vienna, Austria, 2009. URL http://www.R-project.org. ISBN 3-900051-07-0.

  34. 34.

    Saigusa, T. and Kuramoto, Y., “Amoeba anticipate periodic events,” Physical Review Letters, 100, 1, 018101, 2008.

  35. 35.

    Saygin A. P., Cicekli I., Akman V.: “Turing test: 50 years later,”. Minds and Machines 10, 463–518 (2000)

    Article  Google Scholar 

  36. 36.

    Schuster A.: Robust Intelligent Systems. Springer Verlag, London (2008)

    Google Scholar 

  37. 37.

    Scott, T. E., “Knowledge,” in Encyclopedia of Creativity (Pritzker, S. R. and Runco, M. A. eds.), 1, Academic Press, pp. 119–129, 1999.

  38. 38.

    Searle J. R.: “Minds, brains, and programs,”. Behavioral and Brain Sciences 3, 417–457 (1980)

    Article  Google Scholar 

  39. 39.

    Searle, J. R., “The Turing test: 55 years later,” in Parsing the Turing Test: Philosophical and Methodological Issues in the Quest for the Thinking Computer (Epstein, R., Roberts, G. and Beber, G. eds.), pp. 139–150, Springer, 2009.

  40. 40.

    Shannon, C. E. and McCarthy, J., Automata Studies, Princeton University Press, 1956.

  41. 41.

    Tamsir A., Tabor J. J., Voigt C. A.: “Robust multicellular computing using genetically encoded NOR gates and chemical ‘wires,’ ”. Nature 469, 212–216 (2010)

    Article  Google Scholar 

  42. 42.

    Tero A., Kobayashi R., Nakagaki T.: “A mathematical model for adaptive transport network in path finding by true slime mold,”. Journal of Theoretical Biology 244(4), 553–564 (2007)

    MathSciNet  Article  Google Scholar 

  43. 43.

    Turing A. M.: “Computing machinery and intelligence,”. Mind 59, 433–460 (1950)

    MathSciNet  Article  Google Scholar 

  44. 44.

    Turing A. M.: “Intelligent machinery, a heretical theory,”. Philosophia Mathematica (reprinted 1996(4(3), 256–260 (1951)

    Google Scholar 

  45. 45.

    Turing, A. M., “Can digital computers think?” Transcript (with Turing’s annotations) of a talk broadcast on BBC Third Programme, 15 May 1951, available at http://www.turingarchive.org/browse.php/B/5, accessed 20 June 2013, pp. 1–8, 1951.

  46. 46.

    Turing, A. M., Braithwaite, L. C. and Jefferson, A. A., “Can automatic calculating machine be said to think?” Transcript of a broadcast discussion transmitted on BBC Third Programme, 14 and 23 Jan. 1952, between Newman, M. H. A., Turing, A. M., Sir Geoffrey Jefferson and Braithwaite, R. B., Available online from the Turing Digital Archive, available at http://www.turingarchive.org/browse.php/B/6, accessed 20 June 2013, pp. 1–61, 1952.

  47. 47.

    Whitby, B., “The Turing test: AI’s biggest blind alley?” in Machines and Thought: The Legacy of Alan Turing (Millican, P. and Clark, A. eds.), Oxford University Press, pp. 53–62, 1996.

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Correspondence to Daniel Berrar.

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Berrar, D., Konagaya, A. & Schuster, A. Turing Test Considered Mostly Harmless. New Gener. Comput. 31, 241–263 (2013). https://doi.org/10.1007/s00354-013-0401-2

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Keywords

  • Turing Test
  • Imitation Game
  • Machine Intelligence
  • Intelligence Amplification
  • Creativity