The Minimum Intelligent Signal Test (MIST) as an Alternative to the Turing Test

• Authors: Łupkowski Paweł , Jurowska Patrycja
• Languages of publication: EN

Abstracts

EN

The aim of this paper is to present and discuss the issue of the adequacy of the Minimum Intelligent Signal Test (MIST) as an alternative to the Turing Test. MIST has been proposed by Chris McKinstry as a better alternative to Turing’s original idea. Two of the main claims about MIST are that (1) MIST questions exploit commonsense knowledge and as a result are expected to be easy to answer for human beings and difficult for computer programs; and that (2) the MIST design aims at eliminating the problem of the role of judges in the test. To discuss these design assumptions we will present Peter D. Turney’s PMI-IR algorithm which allows for MIST-type questions to be answered. We will also present and discuss the results of our own study aimed at the judge problem for MIST.

Keywords

EN

Turing test; Minimum Intelligent Signal Test; subcognitive questions; commonsense knowledge; Artificial Intelligence

• Publisher: Instytut Filozofii - Uniwersytet Jagielloński
• Journal: Diametros
• Year: 2019
• Volume: 16
• Issue: 59
• Pages: 35-47

Dates

published

2019-03-31

Contributors

author

Łupkowski Paweł

• Paweł Łupkowski, dr hab. Uniwersytet im. Adama Mickiewicza w Poznaniu Zakład Logiki i Kognitywisytki Instytut Psychologii Reasoning Research Group ul. Szamarzewskiego 89a Poznań, 60-568

author

Jurowska Patrycja

• Patrycja Jurowska, mgr Uniwersytet im. Adama Mickiewicza w Poznaniu Instytut Psychologii Reasoning Research Group ul. Szamarzewskiego 89a Poznań, 60-568

References

• Ahn L., Blum M., Hopper N.J., Langford J. (2003), “CAPTCHA: Using Hard AI Problems For Security,” Lecture Notes in Computer Science 2656: 294–311.
• Block N. (1995), “The mind as the software of the brain,” [in:] An Invitation to Cognitive Science – Thinking, E. Smith, D. Osherson, (eds), The MIT Press, London: 377–425.
• Carletta J. (1996), “Assessing Agreement on Classifi cation Tasks: The Kappa Statistic,” Computational Linguistics 22 (2): 249–254.
• Dormehl L. (2016), Thinking Machines. The inside story of Artifi cial Intelligence and our race to build the future, WH-Alley, London.
• Epstein R., Roberts G., Beber G. (eds) (2009), Parsing the Turing Test: Philosophical and Methodological Issues in the Quest for the Thinking Computer, Springer Publishing Company.
• Fetzer J.H. (1995), “Minds and machines: behaviorism, dualism, and beyond,” Stanford Humanities Review 4 (2): 251–265.
• Fetzer J.H. (1997), “Thinking and computing: computers as special kinds of signs,” Minds and Machines 7 (3): 345–364.
• French R. (1990), “Subcogniton and the Limits of the Turing Test,” Mind 99 (393): 53–65.
• French R.M. (2000), “Peeking behind the screen: The unsuspected power of the standard Turing Test,” Journal of Experimental and Theoretical Artifi cial Intelligence 12: 331–340.
• Garner R. (2009), “The Turing hub as a standard for Turing test interfaces,” [in:] Parsing the Turing Test: Philosophical and Methodological Issues in the Quest for the Thinking Computer, R. Epstein, G. Roberts, G. Beber (eds), Springer Publishing Company: 319–324.
• Harnish R.M. (2002), Minds, Brains, Computers. An Historical Introduction to the foundations of Cognitive Science, Blackwell Publishers, Oxford.
• Konar A. (2000), Artifi cial Intelligence and Soft Computing. Behavioral and Cognitive Modeling of the Human Brain, CRC Press, Boca Raton–London–N.Y.–Washington.
• Loebner H. (2009), “How to hold a Turing test contest,” [in:] Parsing the Turing Test: Philosophical and Methodological Issues in the Quest for the Thinking Computer, R. Epstein, G. Roberts, G. Beber (eds), Springer Publishing Company: 173–180.
• Łupkowski P. (2010), Test Turinga. Perspektywa sę dziego, Wydawnictwo Naukowe UAM.
• Łupkowski P. (2011), “A Formal Approach to Exploring the Interrogator’s Perspective in the Turing Test,” Logic and Logical Philosophy 20 (1–2): 139–158.
• Łupkowski P., Wiśniewski A. (2011), “Turing interrogative games,” Minds and Machines 21(3): 435–448.
• Łupkowski P., Rybacka A. (2016), “Non-cooperative Strategies of Players in the Loebner Contest,” Organon F 23 (3): 324–365.
• Mauldin M.L. (1994), “Chatterbots, Tiny Muds, and the Turing test: entering the Loebner Prize competition,” [in:] Proceedings of the 12th National Conference on Artifi cial Intelligence (AAAI-04), Menlo Park (CA): 16–21.
• Mauldin M.L. (2009), “Going undercover: Passing as human; artifi cial interest: A step on the road to AI,” [in:] Parsing the Turing Test: Philosophical and Methodological Issues in the Quest for the Thinking Computer, R. Epstein, G. Roberts, G. Beber (eds), Springer Publishing Company: 413–430.
• McKinstry C. (1997), “Minimum Intelligence Signal Test: an Objective Turing Test,” Canadian Artificial Intelligence 41: 17–18.
• McKinstry C. (2000), “Chris McKinstry Replies: Telescopes, AI And More,” URL = https://slashdot.org/story/00/07/04/2114223/chris-mckinstry-replies-telescopes-ai-and--more. [Accessed 12.12.2017].
• McKinstry C., Dale R., Spivey M.J. (2008), “Action dynamics reveal parallel competition in decision-making,” Psychological Science 19 (1): 22–24.
• McKinstry C. (2009), “Mind as Space: Toward the Automatic Discovery of a Universal Human Semantic-affective Hyperspace – A Possible Subcognitive Foundation of a Computer Program Able to Pass the Turing Test,” [in:] Parsing the Turing Test: Philosophical and Methodological Issues in the Quest for the Thinking Computer, R. Epstein, G. Roberts, G. Beber (eds), Springer Publishing Company: 283–300.
• Newman A.H., Turing A.M., Jefferson G., Braithwaite R.B. (1952), “Can automatic calculating machines be said to think?”, [in:] The Turing Digital Archive (www.turingarchive.org), Contents of AMT/B/6.
• R Core Team (2013), “R: A language and environment for statistical computing. R Foundation for Statistical Computing,” URL = http://www. R-project.org/. [Accessed 20.03.2017].
• Saygin A.P., Cicekli I., Akman V. (2001), “Turing test: 50 years later,” Minds and Machines 10: 463–518.
• Shieber S. (ed) (2004), The Turing Test. Verbal Behavior as the Hallmark of Intelligence, The MIT Press, Cambridge, Massachusetts, London.
• Turing A.M. (1950), “Computing machinery and intelligence,” Mind LIX (236): 443–455.
• Turney D.T. (2001a), “Answering subcognitive Turing test questions: A reply to French,” Journal of Experimental and Theoretical Artifi cial Intelligence 13 (4): 409–419.
• Turney P.D. (2001b), “Mining the web for synonyms: PMI-IR versus LSA on TOEFL,” [in:] Proceedings of European Conference on Machine Learning, Springer, Berlin, Heidelberg: 491–502.
• Viera A.J., Garrett J.M. (2005), “Understanding Interobserver Agreement: The Kappa Statistic,” Family Medicine 37 (5): 360–363.
• Watt S. (2009), “Can people think? Or machines? A unifi ed protocol for Turing testing,” [in:] Parsing the Turing Test: Philosophical and Methodological Issues in the Quest for the Thinking Computer, R. Epstein, G. Roberts, G. Beber (eds), Springer Publishing Company: 301–318

Identifiers

DOI

doi: 10.33392/diam.1125