Added by: Nick Novelli, Contributed by: Susan G. SterrettAbstract: On a literal reading of `Computing Machinery and Intelligence'', Alan Turing presented not one, but two, practical tests to replace the question `Can machines think?'' He presented them as equivalent. I show here that the first test described in that much-discussed paper is in fact not equivalent to the second one, which has since become known as `the Turing Test''. The two tests can yield different results; it is the first, neglected test that provides the more appropriate indication of intelligence. This is because the features of intelligence upon which it relies are resourcefulness and a critical attitude to one''s habitual responses; thus the test''s applicablity is not restricted to any particular species, nor does it presume any particular capacities. This is more appropriate because the question under consideration is what would count as machine intelligence. The first test realizes a possibility that philosophers have overlooked: a test that uses a human''s linguistic performance in setting an empirical test of intelligence, but does not make behavioral similarity to that performance the criterion of intelligence. Consequently, the first test is immune to many of the philosophical criticisms on the basis of which the (so-called) `Turing Test'' has been dismissed.
Comment: This paper provides a good analysis of some of the problems with the Turing Test and how they can be avoided. It can be good to use in teaching the classic Turing 1950 paper on the question of whether a computer could be said to 'think' that considers the role of gender in the imitation game version of the test. It could also contribute to an examination of the concept of intelligence, and machine intelligence in particular.Export citation in BibTeX formatExport text citationView this text on PhilPapersExport citation in Reference Manager formatExport citation in EndNote formatExport citation in Zotero format
Sterrett, Susan G.. Turing’s Two Tests For Intelligence
2000, Minds and Machines 10(4): 541-559.
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