Online research in philosophy

The Turing Test is a verbal-behavioral operational criterion of artificial intelligence. If a machine can participate in question–and–answer conversation adequately enough to deceive an intelligent interlocutor, then it has intelligent information processing abilities. Robert M. French has argued that recent discoveries in cognitive science about subcognitive processes involving associational primings prove that the Turing Test cannot provide a satisfactory criterion of machine intelligence, that Turing's prediction concerning the feasibility of building machines to play the imitation game successfully is false, and that the test should be rejected as ethnocentric and incapable of measuring kinds and degrees of nonhuman intelligence. But French's criticism is flawed, because it requires Turing's sufficient conditional criterion of intelligence to serve as a necessary condition. Turing's Test is defended against these objections, and French's claim that the test ought to be rejected because machines cannot pass it is deemed unscientific, resting on the empirically unwarranted assumption that intelligent machines are possible.

According to the conventional wisdom, Turing (1950) said that computing machines can be intelligent. I don''t believe it. I think that what Turing really said was that computing machines –- computers limited to computing –- can only fake intelligence. If we want computers to become genuinelyintelligent, we will have to give them enough initiative (Turing, 1948, p. 21) to do more than compute. In this paper, I want to try to develop this idea. I want to explain how giving computers more ``initiative'''' can allow them to do more than compute. And I want to say why I believe (and believe that Turing believed) that they will have to go beyond computation before they can become genuinely intelligent.

Since the introduction of the imitation game by Turing in 1950 there has been much debate as to its validity in ascertaining machine intelligence. We wish herein to consider a different issue altogether: granted that a computing machine passes the Turing Test, thereby earning the label of ``Turing Chatterbox'', would it then be of any use (to us humans)? From the examination of scenarios, we conclude that when machines begin to participate in social transactions, unresolved issues of trust and responsibility may well overshadow any raw reasoning ability they possess.

Turing’s Imitation Game is often viewed as a test for theorised machines that could ‘think’ and/or demonstrate ‘intelligence’. However, contrary to Turing’s apparent intent, it can be shown that Turing’s Test is essentially a test for humans only. Such a test does not provide for theorised artificial intellects with human-like, but not human-exact, intellectual capabilities. As an attempt to bypass this limitation, I explore the notion of shifting the goal posts of the Turing Test, and related tests such as the Total Turing Test, away from the exact imitation of human capabilities, and towards communication with humans instead. While the continued philosophical relevance of such tests is open to debate, the outcome is a different class of tests which are, unlike the Turing Test, immune to failure by means of sub-cognitive questioning techniques. I suggest that attempting to instantiate such tests could potentially be more scientifically and pragmatically relevant to some Artificial Intelligence researchers, than instantiating a Turing Test, due to the focus on producing a variety of goal directed outcomes through communicative methods, as opposed to the Turing Test’s emphasis on ‘fooling’ an Examiner.

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.

Let psychologism be the doctrine that whether behavior is intelligent behavior depends on the character of the internal information processing that produces it. More specifically, I mean psychologism to involve the doctrine that two systems could have actual and potential behavior _typical_ of familiar intelligent beings, that the two systems could be exactly alike in their actual and potential behavior, and in their behavioral dispositions and capacities and counterfactual behavioral properties (i.e., what behaviors, behavioral dispositions, and behavioral capacities they would have exhibited had their stimuli differed)--the two systems could be alike in all these ways, yet there could be a difference in the information processing that mediates their stimuli and responses that determines that one is not at all intelligent while the other is fully intelligent.

Ned Block ((1981). Psychologism and behaviorism. Philosophical Review, 90, 5-43.) argued that a behaviorist conception of intelligence is mistaken, and that the nature of an agent's internal processes is relevant for determining whether the agent has intelligence. He did that by describing a machine which lacks intelligence, yet can answer questions put to it as an intelligent person would. The nature of his machine's internal processes, he concluded, is relevant for determining that it lacks intelligence. I argue against Block that it is not the nature of its processes but of its linguistic behavior which is responsible for his machine's lack of intelligence. As I show, not only has Block failed to establish that the nature of internal processes is conceptually relevant for psychology, in fact his machine example actually supports some version of behaviorism. As Wittgenstein has maintained, as far as psychology is concerned, there may be chaos inside.