Self-improving AI: an Analysis [Book Review]
David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jack Alan Reynolds
Learn more about PhilPapers
Minds and Machines 17 (3):249-259 (2007)
Self-improvement was one of the aspects of AI proposed for study in the 1956 Dartmouth conference. Turing proposed a “child machine” which could be taught in the human manner to attain adult human-level intelligence. In latter days, the contention that an AI system could be built to learn and improve itself indefinitely has acquired the label of the bootstrap fallacy. Attempts in AI to implement such a system have met with consistent failure for half a century. Technological optimists, however, have maintained that a such system is possible, producing, if implemented, a feedback loop that would lead to a rapid exponential increase in intelligence. We examine the arguments for both positions and draw some conclusions.
|Keywords||Artificial intelligence Autogeny Bootstrap fallacy Complexity barrier Learning Self-improving|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
References found in this work BETA
Alan M. Turing (1950). Computing Machinery and Intelligence. Mind 59 (October):433-60.
Eric B. Baum (2004). What Is Thought? Cambridge MA: Bradford Book/MIT Press.
Vernor Vinge (1993). The Coming Technological Singularity: How to Survive in the Post-Human Era. Whole Earth Review.
Citations of this work BETA
Roman Yampolskiy & Joshua Fox (2013). Safety Engineering for Artificial General Intelligence. Topoi 32 (2):217-226.
Pierre De Loor, Kristen Manac’H. & Jacques Tisseau (2009). Enaction-Based Artificial Intelligence: Toward Co-Evolution with Humans in the Loop. [REVIEW] Minds and Machines 19 (3):319-343.
Similar books and articles
Saul Traiger (2000). Making the Right Identification in the Turing Test. Minds and Machines 10 (4):561-572.
Huma Shah & Kevin Warwick (2010). From the Buzzing in Turing’s Head to Machine Intelligence Contests. In TCIT 2010 / AISB 2010 Convention.
Robert M. French (1990). Subcognition and the Limits of the Turing Test. Mind 99 (393):53-66.
John R. Lucas (1961). Minds, Machines and Godel. Philosophy 36 (April-July):112-127.
Federica Russo (2010). Are Causal Analysis and System Analysis Compatible Approaches? International Studies in the Philosophy of Science 24 (1):67 – 90.
Adam Drozdek (1998). Human Intelligence and Turing Test. AI and Society 12 (4):315-321.
Larry Hauser (2001). Look Who's Moving the Goal Posts Now. Minds and Machines 11 (1):41-51.
Hillary Jay Kelley (1969). Entropy of Knowledge. Philosophy of Science 36 (2):178-196.
Doug Martin & Peter Singer (2003). A Strategy to Improve Priority Setting in Health Care Institutions. Health Care Analysis 11 (1):59-68.
Added to index2009-01-28
Total downloads54 ( #67,567 of 1,780,773 )
Recent downloads (6 months)4 ( #140,361 of 1,780,773 )
How can I increase my downloads?