The feasibility of Turing's child-machine
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Abstract
According to the philosophers of Artificial Intelligence (AI), Turing Machines and the
Imitation Game are the most important concepts proposed by Alan Turing. The Child-Machine Project, which projects learning machines via digital computers, is less known, although it is no
less important. According to Turing’s project, a programmed machine needs to be a Child-Machine
to turn into an adult mind, one that understands, judges, and distinguishes. In this article, I argue that Turing’s desideratum is not realizable only with algorithms. In the first section, I introduce the
problem, while in the second I briefly analyze concepts such as algorithms, Turing Machines, and their relation. In the third section, I deal with Machine Intelligence and the Child-Machine Project.
In the fourth section, I look at a form of understanding, which is the basis of the Chinese Room Argument: introspection and reflective thinking, two factors that enable the process by which
results are revised. In the fifth section, I analyze why those processes of revision are the stumbling block of classical AI or GOFAI; as I argue, introspection and reflective thinking are the cognitive
faculties that prevent the child-machine from becoming a “thinking adult mind”.
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