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How to Pass a Turing Test

Syntactic Semantics, Natural-Language Understanding, and First-Person Cognition

  • Chapter
The Turing Test

Part of the book series: Studies in Cognitive Systems ((COGS,volume 30))

Abstract

I advocate a theory of “syntactic semantics” as a way of understanding how computers can think (and how the Chinese-Room-Argument objection to the Turing Test can be overcome): (1) Semantics, considered as the study of relationsbetweensymbols and meanings, can be turned into syntax — a study of relationsamongsymbols (including meanings) — and hence syntax (i.e., symbol manipulation) can suffice for the semantical enterprise (contra Searle). (2) Semantics, considered as the process of understanding one domain (by modeling it) in terms of another, can be viewed recursively: The base case of semantic understanding — understanding a domain in terms of itself — is “syntactic understanding.” (3) An internal (or “narrow”), first-person point of view makes an external (or “wide”), third-person point of view otiose for purposes of understanding cognition.

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References

  • Abelson, R.P., 1968, “Simulation of social behavior,” pp. 274–356 inThe Handbook of Social Psychologyvol. 2, 2nd edn., G. Lindzey and E. Aronson, eds., Reading, MA: Addison-Wesley

    Google Scholar 

  • Ackerman, D., 1989, “Penguins,”The New Yorker10 July, 38–67.

    Google Scholar 

  • Associated Press, 1997, “Opponent bytes at offer for draw with Kasparov,”Buffalo News7 May, A7.

    Google Scholar 

  • Baum, L.F., 1900The Wonderful Wizard of OzNew York: Dover (1966 reprint).

    Google Scholar 

  • Berman, J. and Bruckman, A., 1999, “The Turing game,”http://www.cc.gatech.edu/elc/turing/

  • Bunn, J.H., forthcoming, “Universal grammar or common syntax? A critical study of Jackendoff’sPatterns in the Mind ” Minds and Machines.

    Google Scholar 

  • Carnap, R., 1928The Logical Structure of the WorldR.A. George (trans.), Berkeley, CA: University of California Press (1967).

    Google Scholar 

  • Colby, K.M., Hilf, F.D., Weber, S., and Kraemer, H.C., 1972, “Turing-like indistinguishability tests for the validation of a computer simulation of paranoid processes,”Artificial Intelligence3, 199–221.

    Article  Google Scholar 

  • Damasio, A.R., 1989, “Time-locked multiregional retroactivation,”Cognition33, 25–62.

    Article  Google Scholar 

  • Dennett, D.C., 1971, “Intentional systems,”Journal of Philosophy68, 87–106.

    Article  Google Scholar 

  • Ehrlich, K. and Rapaport, W.J., 1997, “A computational theory of vocabulary expansion,” pp. 205–210 inProceedings of the 19th Annual Conference of the Cognitive Science SocietyMahwah, NJ: Erlbaum.

    Google Scholar 

  • Elliott, C. and Brzezinski, J., 1998, “Autonomous agents as synthetic characters,”AI Magazine19, 13–30.

    Google Scholar 

  • Erion, G.J., 2000, “Common sense: An investigation in ontology, epistemology, and moral philosophy,” Ph.D. Diss., Philosophy Department, SUNY Buffalo.

    Google Scholar 

  • Fetzer, J.H., 1994, “Mental algorithms: Are minds computational systems?,”Pragmatics and Cog nition2, 1–29.

    Article  Google Scholar 

  • Fodor, J.A., 1980, “Methodological solipsism considered as a research strategy in cognitive psychology,”Behavioral and Brain Science3, 63–109.

    Article  Google Scholar 

  • Hafner, K., 1999, “Guessing who is online,”The New York TimesJuly 22.

    Google Scholar 

  • Hamad, S., 2000, “Minds, machines and Turing: The indistinguishability of indistinguishables,”Journal of Logic Language and Information 9, this issue.

    Google Scholar 

  • Haugeland, J., 1985Artificial Intelligence: The Very IdeaCambridge, MA: MIT.

    Google Scholar 

  • Hill, R.K., 1994, “Issues of semantics in a semantic-network representation of belief,” Tech. Rep. 94–11, Buffalo: SUNY Buffalo Computer Science Department.

    Google Scholar 

  • Hill, R.K., 1995, “Non-well-founded set theory and the circular semantics of semantic networks,” pp. 375–386 inIntelligent Systems: 3rd Golden West International ConferenceE.A. Yfantis, ed., Dordrecht: Springer Science+Business Media Dordrecht.

    Google Scholar 

  • Hutchins, E., 1995aCognition in the Wild, Cambridge, MA: MIT.

    Google Scholar 

  • Hutchins, E., 1995b, “How a cockpit remembers its speeds,”Cognitive Science19, 265–288. Jackendoff, R., forthcoming, ‘BringingPatternsinto focus: A response to Bunn,“Minds and Machines.

    Google Scholar 

  • Johnson, G., 1997, “Ghost in the chess machine: Brain or box? Think about it,”The New York Times9 May, Al, B4.

    Google Scholar 

  • Julesz, B., 1971Foundations of Cyclopean PerceptionChicago, IL: University of Chicago Press.

    Google Scholar 

  • Jurafsky, D. and Martin, J.H., 2000Speech and Language ProcessingEnglewood Cliffs, NJ: Prentice-Hall.

    Google Scholar 

  • Kearns, J., 1997, “Propositional logic of supposition and assertion,”Notre Dame Journal of Formal Logic38, 325–349.

    Article  Google Scholar 

  • Lassègue, J., 1996, ‘What kind of Turing test did Turing have in mind?,“Tekhnema: Journal of Philosophy and Technology3,http://www.gold.ac.ukltekhnema/3/lassegue/read0l.html

  • Levy, S., 1997, “Man v. machine,”Newsweek5 May, 51–56.

    Google Scholar 

  • Loebner, H.G., 1994, “In response [to Shieber I994a],”CACM37(6), 79–82.

    Google Scholar 

  • Maida, A.S. and Shapiro, S.C., 1982, “Intensional concepts in propositional semantic networks,”Cognitive Science6, 291–330.

    Article  Google Scholar 

  • Maloney, J.C., 1987, “The right stuff,”Synthese70, 349–372.

    Article  Google Scholar 

  • Manin, Yu.I., 1977A Course in Mathematical LogicNew York: Springer-Verlag.

    Google Scholar 

  • McGilvray, J., 1998, “Meanings are syntactically individuated and found in the head,”Mind and Language13, 225–280.

    Article  Google Scholar 

  • Morris, C., 1938Foundations of the Theory of SignsChicago, IL: Unversity of Chicago Press.

    Google Scholar 

  • Percy, W., 1975The Message in the BottleNew York: Farrar, Straus and Giroux.

    Google Scholar 

  • Quillian, M.R., 1967, “Word concepts: A theory and simulation of some basic semantic capabilities,”Behavioral Science12, 410–430.

    Google Scholar 

  • Quine, W.V.O., 1951, “Two dogmas of empiricism,” reprinted inFrom a Logical Point of View2nd edn., Rev., Cambridge, MA: Harvard University Press, 1980, pp. 20–46.

    Google Scholar 

  • Rapaport, W.J., 1978, “Meinongian theories and a Russellian paradox,”Noûs12, 153–180; errata, 1979,Noûs13, 125.

    Article  Google Scholar 

  • Rapaport, W.J., 1981, “How to make the world fit our language: An essay in Meinongian semantics,”Grazer Philosophische Studien14, 1–21.

    Google Scholar 

  • Rapaport, W.J., 1985, “Machine understanding and data abstraction in Searle’s Chinese Room,” pp. 341–345 inProceedings of the 7th Annual Conference of the Cognitive Science SocietyHillsdale, NJ: Erlbaum.

    Google Scholar 

  • Rapaport, W.J., 1986a, “Philosophy, artificial intelligence, and the Chinese-Room Argument,”Abacus3, Summer, 6–17; correspondence, 1987,Abacus4, Winter, 6–7,Abacus4, Spring, 5–7.

    Google Scholar 

  • Rapaport, W.J., 1986b, “Searle’s experiments with thought,”Philosophy of Science53, 271–279.

    Article  Google Scholar 

  • Rapaport, W.J., 1988a, “To think or not to think,”Noûs22, 585–609.

    Article  Google Scholar 

  • Rapaport, W.J., 1988b, “Syntactic semantics: Foundations of computational natural-language understanding,” pp. 81–131 inAspects of Artificial IntelligenceJ.H. Fetzer, ed., Dordrecht: Springer Science+Business Media Dordrecht.

    Google Scholar 

  • Rapaport, W.J., 1995, “Understanding understanding: Syntactic semantics and computational cognition,” pp. 49–88 inAl Connectionism,and Philosophical PsychologyJ.E. Tomberlin, ed., Phil. Perspectives, Vol. 9, Atascadero, CA: Ridgeview.

    Google Scholar 

  • Rapaport, W.J., 1996Understanding Understanding: Semantics Computation and CognitionTech. Rep. 96–26, Buffalo: SUNY Buffalo Computer Science Department;http://www.cse.buffalo.edu/tech-reports/96–26.ps.Z

  • Rapaport, W.J., 1998, “How minds can be computational systems,”Journal of Experimental Theoretical and Artificial Intelligence 10, 403–419.

    Article  Google Scholar 

  • Rapaport, W.J., 1999, “Implementation is semantic interpretation,”The Monist82, 109–130.

    Google Scholar 

  • Rapaport, W.J. and Ehrlich, K., 2000, “A computational theory of vocabulary acquisition,” inNatural Language Processing and Knowledge RepresentationL. Iwafiska and S.C. Shapiro, eds., Menlo Park, CA/Cambridge, MA: AAAI/MIT (in press).

    Google Scholar 

  • Schonberg, H.C., 1989, “Kasparov beats chess computer (for now),”New York Times23 October, Al, B2.

    Google Scholar 

  • Searle, J.R., 1980, “Minds, brains, and programs,”Behavioral and Brain Science3, 417–457.

    Article  Google Scholar 

  • Searle, J.R., 1982, “The myth of the computer,”New York Review of Books29 April, 3–6; cf. correspondence, same journal, 24 June 1982, 56–57.

    Google Scholar 

  • Shapiro, S.C., 1979, “The SNePS semantic network processing system,” pp. 179–203 inAssociative NetworksN. Findler, ed., New York: Academic Press.

    Google Scholar 

  • Shapiro, S.C., 1995, “Computationalism,”Minds and Machines5, 517–524.

    Article  Google Scholar 

  • Shapiro, S.C., 1997, “What is computer science?,”http://www.cse.buffalo.edu/-shapiro/Papers/whatiscs.pdf

  • Shapiro, S.C., 1998, “Embodied Cassie,” pp. 136–143 inCognitive Robotics: Papers from the 1998 AAAI Fall SymposiumTech. Rep. FS-98–02, Menlo Park, CA: AAAI.

    Google Scholar 

  • Shapiro, S.C. and Rapaport, W.J., 1987, “SNePS considered as a fully intensional propositional semantic network,” pp. 262–315 inThe Knowledge FrontierN. Cercone and G. McCalla, eds., New York: Springer-Verlag.

    Google Scholar 

  • Shapiro, S.C. and Rapaport, W.J., 1991, “Models and minds: Knowledge representation for natural-language competence,” pp. 215–259 inPhilosophy and AIR. Cummins and J. Pollock, eds., Cambridge, MA: MIT.

    Google Scholar 

  • Shapiro, S.C. and Rapaport, W.J., 1992, “The SNePS family,”Computers and Marhenanics with Applications23, 243–275.

    Article  Google Scholar 

  • Shapiro, S.C. and Rapaport, W.J., 1995, “An introduction to a computational reader of narrative,” pp. 79–105 inDeixis in NarrativeJ.F. Duchan, G.A. Bruder, and L.E. Hewitt, eds., Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • Shieber, S.M., 1994a, “Lessons from a restricted Turing test,”CACM37(6), 70–78.

    Google Scholar 

  • Shieber, S.M., 1994b, “On Loebner’s lessons,”CACM37, 83–84.

    Google Scholar 

  • Simon, H.A. and Newell, A., 1958, “Heuristic problem solving: The next advance in operations research,”Operations Research6(6), 1–10.

    Article  Google Scholar 

  • Simpson, J.A. and Weiner, E.S.C. (preparers), 1989The Oxford English Dictionary,2nd edn., Oxford: Clarendon.

    Google Scholar 

  • Smith, B.C., 1987, “The correspondence continuum,” Report CSLI-87–71, Stanford, CA: CSLI. Srihari, R.K., 1991, “PICTION: A system that uses captions to label human faces in newspaper photographs,” pp. 80–85 inProceedings of the 9th National Conference on Artificial Intelligence(AAA/—9/), Menlo Park, CA: AAAI/MIT.

    Google Scholar 

  • Srihari, R.K. and Rapaport, W.J., 1989, “Extracting visual information from text: Using captions to label human faces in newspaper photographs,” pp. 364–371 inProceedings of the 11 th Annual Conference of the Cognitive Science SocietyHillsdale, NJ: Erlbaum.

    Google Scholar 

  • Stork, D.G., 1997HAL’s LegacyCambridge, MA: MIT.

    Google Scholar 

  • Thagard, P., 1986, “Parallel computation and the mind-body problem,”Cognitive Science 10301–318.

    Google Scholar 

  • Turing, A.M., 1936, “On computable numbers, with an application to theEntscheidungsproblem”;reprinted, with corrections, 1965 in The Undecidable, M. Davis, ed., New York: Raven, pp. 116–154.

    Google Scholar 

  • Turing, A.M., 1950, “Computing machinery and intelligence,”Mind59, 433–460.

    Google Scholar 

  • Wartofsky, M.W., 1966, “The model muddle,” pp. 1–11 inModels: Representation and the Scientific UnderstandingDordrecht: Reidel (1979).

    Google Scholar 

  • Weizenbaum, J., 1966, “ELIZA — A computer program for the study of natural language communication between man and machine,”CACM9, 36–45.

    Google Scholar 

  • Williams, B., 1998, “The end of explanation?,”The New York Review of Books45, 40–44 (19 November).

    Google Scholar 

  • Woods, W.A., 1975, “What’s in a link,” pp. 35–82 inRepresentation and UnderstandingD.G. Bobrow and A.M. Collins, eds., New York: Academic Press.

    Google Scholar 

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Department of Philosophy, and Center for Cognitive Science, State University of New York at Buffalo, Buffalo, NY, 14260-2000, USA

    William J. Rapaport

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  1. William J. Rapaport
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Editors and Affiliations

  1. Dartmouth College, Hanover, USA

    James H. Moor

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Rapaport, W.J. (2003). How to Pass a Turing Test. In: Moor, J.H. (eds) The Turing Test. Studies in Cognitive Systems, vol 30. Springer, Dordrecht. https://doi.org/10.1007/978-94-010-0105-2_9

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  • DOI: https://doi.org/10.1007/978-94-010-0105-2_9

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