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Title Self-improving AI: an Analysis
Edition Volume 17, Number 3
Call Number
ISBN/ISSN 0924-6495
Author(s) Hall,John Storrs
Subject(s)
Classification
Series Title Minds and Machines
GMD Electronic Journal
Language English
Publisher Springer Netherlands
Publishing Year 2007
Publishing Place Netherlands
Collation 11p
Abstract/Notes 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.
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