New Generation Computing

, Volume 31, Issue 4, pp 241–263 | Cite as

Turing Test Considered Mostly Harmless

  • Daniel Berrar
  • Akihiko Konagaya
  • Alfons Schuster


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.


Turing Test Imitation Game Machine Intelligence Intelligence Amplification Creativity 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Abramson D.: “Turing’s responses to two objections,”. Minds & Machines 18, 147–167 (2008)CrossRefGoogle 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.Google Scholar
  4. 4.
    Berrar, D., “Revisiting the Turing test from a statistical angle,” International Symposium on Soft Computing, Yokohama, Japan, pp. 1–4, 2012Google Scholar
  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.Google Scholar
  7. 7.
    Block N.: “Psychologism and behaviorism,”. Philosophical Review 1, 5–43 (1981)MathSciNetCrossRefGoogle 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.Google Scholar
  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)CrossRefGoogle Scholar
  11. 11.
    Bringsjord S., Bello P., Ferrucci D.: “Creativity, the Turing test, and the (better) Lovelace test,”. Minds & Machines 11, 3–27 (2001)CrossRefzbMATHGoogle 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.Google Scholar
  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)CrossRefGoogle 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.Google Scholar
  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, 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)CrossRefGoogle Scholar
  18. 18.
    French R.: “Subcognition and the limits of the Turing test,”. Mind 99, 53–65 (1990)MathSciNetCrossRefGoogle Scholar
  19. 19.
    French R.: “Dusting off the Turing test,”. Science 336, 164–165 (2012)CrossRefGoogle Scholar
  20. 20.
    Harel D.: “A Turing-like test for biological modeling,”. Nature Biotechnology 23(4), 495–496 (2005)CrossRefGoogle 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.Google Scholar
  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.Google Scholar
  23. 23.
    Hodges A.: “Beyond Turing’s machines,”. Science 336, 163–164 (2012)CrossRefGoogle 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)CrossRefGoogle 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)CrossRefGoogle 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)CrossRefGoogle Scholar
  28. 28.
    Martin, R. M., Philosophical Conversations, Broadview Press Ltd., 2008.Google Scholar
  29. 29.
    Mednick S. A.: “The associative basis of the creative process,”. Psychological Review 69(3), 220–232 (1962)CrossRefGoogle Scholar
  30. 30.
    Miller M. B., Bassler B. L.: “Quorum sensing in bacteria,”. Annual Reviews in Microbiology 55, 165–199 (2005)CrossRefGoogle Scholar
  31. 31.
    Nakagaki, T., Yamada, H. and Tóth, A., “Maze-solving by an amoeboid organism,” Nature, 407 (6803), 470, 2000.Google Scholar
  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)CrossRefGoogle Scholar
  33. 33.
    R Development Core Team, “R: A Language and Environment for Statistical Computing,” R Foundation for Statistical Computing, Vienna, Austria, 2009. URL ISBN 3-900051-07-0.
  34. 34.
    Saigusa, T. and Kuramoto, Y., “Amoeba anticipate periodic events,” Physical Review Letters, 100, 1, 018101, 2008.Google Scholar
  35. 35.
    Saygin A. P., Cicekli I., Akman V.: “Turing test: 50 years later,”. Minds and Machines 10, 463–518 (2000)CrossRefGoogle Scholar
  36. 36.
    Schuster A.: Robust Intelligent Systems. Springer Verlag, London (2008)CrossRefGoogle 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.Google Scholar
  38. 38.
    Searle J. R.: “Minds, brains, and programs,”. Behavioral and Brain Sciences 3, 417–457 (1980)CrossRefGoogle 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.Google Scholar
  40. 40.
    Shannon, C. E. and McCarthy, J., Automata Studies, Princeton University Press, 1956.Google Scholar
  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)CrossRefGoogle 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)MathSciNetCrossRefGoogle Scholar
  43. 43.
    Turing A. M.: “Computing machinery and intelligence,”. Mind 59, 433–460 (1950)MathSciNetCrossRefGoogle 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, 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, 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.Google Scholar

Copyright information

© Ohmsha and Springer Japan 2013

Authors and Affiliations

  • Daniel Berrar
    • 1
  • Akihiko Konagaya
    • 1
  • Alfons Schuster
    • 2
  1. 1.Interdisciplinary Graduate School of Science and EngineeringTokyo Institute of TechnologyYokohamaJapan
  2. 2.Faculty of International Research and EducationWaseda UniversityTokyoJapan

Personalised recommendations