MacInnes, W. J.*, Armstrong, B. C., Pare, D., Cree, G. S., & Joordens, S. (2009). Everyone’s a critic: Memory models and uses for an artificial Turing judge.   In B. Goertzel, M. Hutter, & P. Hitzler (Eds.) Proceedings of the Second Conference on Artificial General Intelligence (pp. 132-137).  Paris, France: Atlantic Press.   

***Second runner up for Kurzweil Best Artificial General Intelligence Paper at AGI 2009 ***


Author's self-archived version (.pdf)  (6 pages)

Official version from the Association for the Advancement of Artificial Intelligence [external link]

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**Video recording of the talk ** [external link to copy cached by the society]

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The Turing test was originally conceived by Alan Turing (1950, Mind) to determine if a machine had achieved human-level intelligence.  Although no longer taken as a comprehensive measure of human intelligence, passing the Turing test remains an interesting challenge as evidenced by the still unclaimed Loebner prize, a high profile prize for the first AI to pass a Turing style test. In this paper, we sketch the development of an artificial “Turing judge” capable of critically evaluating the likelihood that a stream of discourse was generated by a human or a computer. The knowledge our judge uses to make the assessment comes from a model of human lexical semantic memory known as latent semantic analysis (Landauer & Dumais, 1997; Psych. Rev.). We provide empirical evidence that our implemented judge is capable of distinguishing between human and computer generated language from the Loebner Turing test competition with a degree of success similar to human judges.

Keywords: Semantic Memory, General Knowledge, Decision Making, Machine learning, Language, Turing test

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