Everyone's a Critic: Memory Models and Uses for an Artificial Turing Judge

DOI

10.2991/agi.2009.34How to use a DOI?

Abstract

The Turing test was originally conceived by Alan Turing [20] 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[7], 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[9]. 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.

Copyright

© 2009, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - W. Joseph MacInnes
AU  - Blair C. Armstrong
AU  - Dwayne Pare
AU  - George S. Cree
AU  - Steve Joordens
PY  - 2009/06
DA  - 2009/06
TI  - Everyone's a Critic: Memory Models and Uses for an Artificial Turing Judge
BT  - Proceedings of the 2nd Conference on Artificial General Intelligence (2009)
PB  - Atlantis Press
SP  - 158
EP  - 163
SN  - 1951-6851
UR  - https://doi.org/10.2991/agi.2009.34
DO  - 10.2991/agi.2009.34
ID  - MacInnes2009/06
ER  -