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  1. The Genius of the 'Original Imitation Game' Test.S. G. Sterrett - 2020 - Minds and Machines 30 (4):469-486.
    Twenty years ago in "Turing's Two Tests for Intelligence" I distinguished two distinct tests to be found in Alan Turing's 1950 paper "Computing Machinery and Intelligence": one by then very well-known, the other neglected. I also explained the significance of the neglected test. This paper revisits some of the points in that paper and explains why they are even more relevant today. It also discusses the value of tests for machine intelligence based on games humans play, giving an analysis of (...)
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  • Nested Algorithms and "The Original Imitation Game Test": A Reply to James Moor.Susan G. Sterrett - 2002 - Minds and Machines 12 (1):131-136.
    In "The Status and Future of the Turing Test" (Moor, 2001), which appeared in an earlier issue of this journal, James Moor remarks on my paper "Turing's Two Tests for Intelligence." In my paper I had claimed that, whatever Turing may or may not have thought, the test described in the opening section of Turing's now legendary 1950 paper "Computing Machinery and Intelligence" is not equivalent to, and in fact is superior to, the test described in a passage that occurs (...)
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  • Abduction and Estimation in Animals.Woosuk Park - 2012 - Foundations of Science 17 (4):321-337.
    One of the most pressing issues in understanding abduction is whether it is an instinct or an inference. For many commentators find it paradoxical that new ideas are products of an instinct and products of an inference at the same time. Fortunately, Lorenzo Magnani’s recent discussion of animal abduction sheds light on both instinctual and inferential character of Peircean abduction. But, exactly for what reasons are Peirce and Magnani so convinced that animal abduction can provide us with a novel perspective? (...)
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  • The Questioning Turing Test.Nicola Damassino - 2020 - Minds and Machines 30 (4):563-587.
    The Turing Test is best regarded as a model to test for intelligence, where an entity’s intelligence is inferred from its ability to be attributed with ‘human-likeness’ during a text-based conversation. The problem with this model, however, is that it does not care if or how well an entity produces a meaningful conversation, as long as its interactions are humanlike enough. As a consequence, the TT attracts projects that concentrate on how best to fool the judges. In light of this, (...)
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