I propose to consider the question, "Can machines think?" This should begin with definitions of the meaning of the terms "machine" and "think." The definitions might be framed so as to reflect so far as possible the normal use of the words, but this attitude is dangerous, If the meaning of the words "machine" and "think" are to be found by examining how they are commonly used it is difficult to escape the conclusion that the meaning and the answer to (...) the question, "Can machines think?" is to be sought in a statistical survey such as a Gallup poll. But this is absurd. Instead of attempting such a definition I shall replace the question by another, which is closely related to it and is expressed in relatively unambiguous words. The new form of the problem can be described in terms of a game which we call the 'imitation game." It is played with three people, a man (A), a woman (B), and an interrogator (C) who may be of either sex. The interrogator stays in a room apart front the other two. The object of the game for the interrogator is to determine which of the other two is the man and which is the woman. He knows them by labels X and Y, and at the end of the game he says either "X is A and Y is B" or "X is B and Y is A." The interrogator is allowed to put questions to A and B. We now ask the question, "What will happen when a machine takes the part of A in this game?" Will the interrogator decide wrongly as often when the game is played like this as he does when the game is played between a man and a woman? These questions replace our original, "Can machines think?". (shrink)
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This paper concerns AlanTuring’s ideas about machines, mathematical methods of proof, and intelligence. By the late 1930s, Kurt Gödel and other logicians, including Turing himself, had shown that no finite set of rules could be used to generate all true mathematical statements. Yet according to Turing, there was no upper bound to the number of mathematical truths provable by intelligent human beings, for they could invent new rules and methods of proof. So, the output of (...) a human mathematician, for Turing, was not a computable sequence (i.e., one that could be generated by a Turing machine). Since computers only contained a finite number of instructions (or programs), one might argue, they could not reproduce human intelligence. Turing called this the “mathematical objection” to his view that machines can think. Logico-mathematical reasons, stemming from his own work, helped to convince Turing that it should be possible to reproduce human intelligence, and eventually compete with it, by developing the appropriate kind of digital computer. He felt it should be possible to program a computer so that it could learn or discover new rules, overcoming the limitations imposed by the incompleteness and undecidability results in the same way that human mathematicians presumably do. (shrink)
As is well known, AlanTuring drew a line, embodied in the "Turing test," between intellectual and physical abilities, and hence between cognitive and natural sciences. Less familiarly, he proposed that one way to produce a "passer" would be to educate a "child machine," equating the experimenter's improvements in the initial structure of the child machine with genetic mutations, while supposing that the experimenter might achieve improvements more expeditiously than natural selection. On the other hand, in his (...) foundational "On the chemical basis of morphogenesis," Turing insisted that biological explanation clearly confine itself to purely physical and chemical means, eschewing vitalist and teleological talk entirely and hewing to D'Arcy Thompson's line that "evolutionary 'explanations,'" are historical and narrative in character, employing the same intentional and teleological vocabulary we use in doing human history, and hence, while perhaps on occasion of heuristic value, are not part of biology as a natural science. To apply Turing's program to recent issues, the attempt to give foundations to the social and cognitive sciences in the "real science" of evolutionary biology (as opposed to Turing's biology) is neither to give foundations, nor to achieve the unification of the social/cognitive sciences and the natural sciences. (shrink)
In his short life, AlanTuring (1912-1954) made foundational contributions to philosophy, mathematics, biology, artificial intelligence, and computer science. He, as much as anyone, invented the digital electronic computer. From September, 1939 much of his work on computation was war-driven and brutally practical. He developed high speed computing devices needed to decipher German Enigma Machine messages to and from U-boats, countering the most serious threat by far to Britain's survival during World War Two. Yet few people have an (...) image of him. (shrink)
In his short life, <span class='Hi'>Alan</span> Turing (1912-1954) made foundational contributions to philosophy, mathematics, biology, artificial intelligence, and computer science. He, as much as anyone, invented and showed how to program the digital electronic computer. From September, 1939, his work on computation was war-driven and brutally practical. He developed high speed computing devices needed to decipher German Enigma Machine messages to and from U-boats, countering the most serious threat by far to Britain=s survival during World War Two.
I live just off of Bell Road outside of Newburgh, Indiana, a small town of 3,000 people. A mile down the street Bell Road intersects with Telephone Road not as a modern reminder of a technology belonging to bygone days, but as testimony that this technology, now more than a century and a quarter old, is still with us. In an age that prides itself on its digital devices and in which the computer now equals the telephone as a medium (...) of communication, it is easy to forget the debt we owe to an era that industrialized the flow of information, that the light bulb, to pick a singular example, which is useful for upgrading visual information we might otherwise overlook, nonetheless remains the most prevalent of all modern day information technologies. Edison’s light bulb, of course, belongs to a different order of informational devices than the computer, but not so the telephone, not entirely anyway. AlanTuring, best known for his work on the Theory of Computation (1937), the Turing Machine (also 1937) and the Turing Test (1950), is often credited with being the father of computer science and the father of artificial intelligence. Less well-known to the casual reader but equally important is his work in computer engineering. The following lecture on the Automatic Computing Engine, or ACE, shows Turing in this different light, as a mechanist concerned with getting the greatest computational power from minimal hardware resources. Yet Turing’s work on mechanisms is often eclipsed by his thoughts on computability and his other theoretical interests. This is unfortunate for several reasons, one being that it obscures our picture of the historical trajectory of information technology, a second that it emphasizes a false dichotomy between “hardware” and “software” to which Turing himself did not ascribe but which has, nonetheless, confused researchers who study the nature of mind and intelligence for generations.. (shrink)
In his short life, AlanTuring (1912-1954) made foundational contributions to philosophy, mathematics, biology, artificial intelligence, and computer science. He, as much as anyone, invented and showed how to program the digital electronic computer. From September, 1939, his work on computation was war-driven and brutally practical. He developed high speed computing devices needed to decipher German Enigma Machine messages to and from U-boats, countering the most serious threat by far to Britain..
The origin of my article lies in the appearance of Copeland and Proudfoot's feature article in Scientific American, April 1999. This preposterous paper, as described on another page, suggested that Turing was the prophet of 'hypercomputation'. In their references, the authors listed Copeland's entry on 'The Church-Turing thesis' in the Stanford Encyclopedia. In the summer of 1999, I circulated an open letter criticising the Scientific American article. I included criticism of this Encyclopedia entry. This was forwarded (by Prof. (...) Sol Feferman) to Prof. Ed Zalta, editor of the Encyclopedia, and after some discussion he invited me to submit an entry on 'AlanTuring.'. (shrink)
It seems opportune to commemorate in ‘Augustinianum’ the centenary of the birth of AlanTuring, insofar as he is an outstanding figure whose theoritical insight gave birth to the computer revolution of the twentieth centur y. His theories are equally important for the methodology supporting studies in the humanities.
The mathematical genius AlanTuring (1912-1954) was one of the greatest scientists and thinkers of the 20th century. Now well known for his crucial wartime role in breaking the ENIGMA code, he was the first to conceive of the fundamental principle of the modern computer-the idea of controlling a computing machine's operations by means of a program of coded instructions, stored in the machine's 'memory'. In 1945 Turing drew up his revolutionary design for an electronic computing machine-his (...) Automatic Computing Engine ('ACE'). A pilot model of the ACE ran its first program in 1950 and the production version, the 'DEUCE', went on to become a cornerstone of the fledgling British computer industry. The first 'personal' computer was based on Turing's ACE. -/- AlanTuring's Automatic Computing Engine describes Turing's struggle to build the modern computer. The first detailed history of Turing's contributions to computer science, this text is essential reading for anyone interested in the history of the computer and the history of mathematics. It contains first hand accounts by Turing and by the pioneers of computing who worked with him. As well as relating the story of the invention of the computer, the book clearly describes the hardware and software of the ACE-including the very first computer programs. The book is intended to be accessible to everyone with an interest in computing, and contains numerous diagrams and illustrations as well as original photographs. -/- The book contains chapters describing Turing's path-breaking research in the fields of Artificial Intelligence (AI) and Artificial Life (A-Life). The book has an extensive system of hyperlinks to The Turing Archive for the History of Computing, an on-line library of digital facsimiles of typewritten documents by Turing and the other scientists who pioneered the electronic computer. (shrink)
This is the second of two volumes of essays in commemoration of AlanTuring; it celebrates his intellectual legacy within the philosophy of mind and cognitive science. A distinguished international cast of contributors focus on the relationship beteen a scientific, computational image of the mind and a common-sense picture of the mind as an inner arena populated by concepts, beliefs, intentions, and qualia. Topics covered include the causal potency of folk-psychological states, the connectionist reconception of learning and concept (...) formation, the understanding of the notion of computation itself, and the relation between philosophical and psychological theories of concepts. -/- Also available in paperback is the companion volume, Machines and Thought, edited by Peter Millican and Andy Clark, which focuses on Turing's main innovations in artificial intelligence. (shrink)
This is the first of two volumes of essays in commemoration of AlanTuring, whose pioneering work in the theory of artificial intelligence and computer science continues to be widely discussed today. A group of prominent academics from a wide range of disciplines focus on three questions famously raised by Turing: What, if any, are the limits on machine 'thinking'? Could a machine be genuinely intelligent? Might we ourselves be biological machines, whose thought consists essentially in nothing (...) more than the interaction of neurons according to strictly determined rules? The discussion of these fascinating issues is accessible to non-specialists and stimulating for all readers. -/- Also available in paperback is the companion volume: Connectionism, Concepts, and Folk Psychology, edited by Andy Clark and Peter Millican. While Volume 1 concentrates on Turing's main innovations in artificial intelligence, Volume 2 looks more broadly at his intellectual legacy in philosophy and cognitive science. (shrink)
A. M. Turing has bequeathed us a conceptulary including 'Turing, or Turing-Church, thesis', 'Turing machine', 'universal Turing machine', 'Turing test' and 'Turing structures', plus other unnamed achievements. These include a proof that any formal language adequate to express arithmetic contains undecidable formulas, as well as achievements in computer science, artificial intelligence, mathematics, biology, and cognitive science. Here it is argued that these achievements hang together and have prospered well in the 50 years since (...)Turing's death. (shrink)
It is not widely realised that Turing was probably the first person to consider building computing machines out of simple, neuron-like elements connected together into networks in a largely random manner. Turing called his networks unorganised machines. By the application of what he described as appropriate interference, mimicking education an unorganised machine can be trained to perform any task that a Turing machine can carry out, provided the number of neurons is sufficient. Turing proposed simulating both (...) the behaviour of the network and the training process by means of a computer program. We outline Turing's connectionist project of 1948. (shrink)
AlanTuring advocated a kind of functionalism: A machine M is a thinker provided that it responds in certain ways to certain inputs. Davidson argues that Turing’s functionalism is inconsistent with a certain kind of epistemic externalism, and is therefore false. In Davidson’s view, concepts consist of causal liasons of a certain kind between subject and object. Turing’s machine doesn’t have the right kinds of causal liasons to its environment. Therefore it doesn’t have concepts. Therefore it (...) doesn’t think. I argue that this reasoning is entirely fallacious. It is true that, in some cases, a causal liason between subject and object is part of one’s concept of that object. Consequently, to grasp certain propositions, one must have certain kids of causal ties to one’s environment. But this means that we must rethink some old views on what rationality is. It does not mean, pace Davidson, that a precondition for being rational is being causally embedded in one’s environment in a certain way. If Turing’s machine isn’t capable of thinking (I leave it open whether it is or is not), that has nothing to do with its lacking certain kinds of causal connections to the environment. The larger significance of our discussion is this: rationality consists either in one’s ability to see the bearing of purely existential propositions on one another or rationality is simply not to be understood as the ability see the bearing that propositions have on one another. (shrink)
We investigate Turing's contributions to computability theory for real numbers and real functions presented in [22, 24, 26]. In particular, it is shown how two fundamental approaches to computable analysis, the so-called ‘Type-2 Theory of Effectivity' (TTE) and the ‘realRAM machine' model, have their foundations in Turing's work, in spite of the two incompatible notions of computability they involve. It is also shown, by contrast, how the modern conceptual tools provided by these two paradigms allow a systematic interpretation (...) of Turing's pioneering work in the subject. (shrink)
Englantilaisen yleisneron Alan Turingin kuoleman yllä lepää salaperäisyyden verho. On hyvin mahdollista, ettei kenenkään muun nykyajan ajattelijan kuolemaan liity yhtä paljon legendoja ja spekulaatioita. Kiistattomat tosiasiat ovat lyhykäisyydessään seuraavat: siivooja löysi Turingin kotoaan kuolleena 8. kesäkuuta 1954. Turingin todettiin kuolleen edellisenä iltana syanidimyrkytykseen, ja hänen viereltään löytyi puoliksi syöty omena. Hän oli kuollessaan 41-vuotias. Loppu on enemmän tai vähemmän arvailujen varassa.
Almost everything Turing wrote is now accessible on-line in some form, much of it in the Turing Digital Archive, which makes available scanned versions of the physical papers held in the archive at King's College, Cambridge University. See..
It is not widely realised that Turing was probably the first person to consider building computing machines out of simple, neuron-like elements connected together into networks in a largely random manner. Turing called his networks 'unorganised machines'. By the application of what he described as 'appropriate interference, mimicking education' an unorganised machine can be trained to perform any task that a Turing machine can carry out, provided the number of 'neurons' is sufficient. Turing proposed simulating both (...) the behaviour of the network and the training process by means of a computer program. We outline Turing's connectionist project of 1948. (shrink)
On the 27th of October, 1949, the Department of Philosophy at the University of Manchester organized a symposium "Mind and Machine", as Michael Polanyi noted in his Personal Knowledge (1974, p. 261). This event is known, especially among scholars of AlanTuring, but it is scarcely documented. Wolfe Mays (2000) reported about the debate, which he personally had attended, and paraphrased a mimeographed document that is preserved at the Manchester University archive. He forwarded a copy to Andrew Hodges (...) and B. Jack Copeland, who in then published it on their respective websites. The basis of this interpretation here is the copy preserved in the Regenstein Library of the University of Chicago, Special Collections, Polanyi Collection (abbreviated RPC, box 22, folder 19). The same collection holds the mimeographed statement that Polanyi prepared for this symposium: "Can the mind be represented by a machine?" This text has not been studied by Polanyi scholars. (shrink)
In this paper I argue that Turing’s responses to the mathematical objection are straightforward, despite recent claims to the contrary. I then go on to show that by understanding the importance of learning machines for Turing as related not to the mathematical objection, but to Lady Lovelace’s objection, we can better understand Turing’s response to Lady Lovelace’s objection. Finally, I argue that by understanding Turing’s responses to these objections more clearly, we discover a hitherto unrecognized, substantive (...) thesis in his philosophical thinking about the nature of mind. (shrink)