A. M. Turing () Computing Machinery and Intelligence. Mind . It may also be said that this identification of machines with digital computers, like our. Computing Machinery and Intelligence. Author(s): A. M. Turing. Source: Mind, New Series, Vol. 59, No. (Oct., ), pp. Published by: Oxford. A. M. TURING; I.—COMPUTING MACHINERY AND INTELLIGENCE, Mind, Volume LIX, Issue , 1 October , This content is only available as a PDF .
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"Computing Machinery and Intelligence" is a seminal paper written by Alan Turing on the topic .. Turing, Alan (October ), "Computing Machinery and Intelligence" (PDF), Mind, LIX (): –, doi/mind/LIX; Saygin. Mind, Computing Machinery and Intelligence. By raudone.info Presentation for AI course by Koo sang jun. 1. Page 2. Contents. ▻ About Alan MathisonTuring. Computing Machinery and Intelligence Mind vol. Universal Turing Machine. R.I.P.. Abstract. In recent years, much research has been devoted.
He points out that a human clone , while man-made, would not provide a very interesting example.
Turing suggested that we should focus on the capabilities of digital machinery—machines which manipulate the binary digits of 1 and 0, rewriting them into memory using simple rules. He gave two reasons. First, there is no reason to speculate whether or not they can exist. They already did in Second, digital machinery is "universal". Turing's research into the foundations of computation had proved that a digital computer can, in theory, simulate the behaviour of any other digital machine, given enough memory and time.
This is the essential insight of the Church—Turing thesis and the universal Turing machine. Therefore, if any digital machine can "act like it is thinking" then, every sufficiently powerful digital machine can. Turing writes, "all digital computers are in a sense equivalent.
Turing now restates the original question as "Let us fix our attention on one particular digital computer C. Is it true that by modifying this computer to have an adequate storage, suitably increasing its speed of action, and providing it with an appropriate programme, C can be made to play satisfactorily the part of A in the imitation game, the part of B being taken by a man? Nine common objections[ edit ] See also: Philosophy of artificial intelligence Having clarified the question, Turing turned to answering it: he considered the following nine common objections, which include all the major arguments against artificial intelligence raised in the years since his paper was first published.
Let us hope and believe that they cannot do so.
This objection is a fallacious appeal to consequences , confusing what should not be with what can or cannot be Wardrip-Fruin, Turing suggests that humans are too often wrong themselves and pleased at the fallibility of a machine. This argument would be made again by philosopher John Lucas in and physicist Roger Penrose in He adds, "I do not wish to give the impression that I think there is no mystery about consciousness Turing's reply is now known as the " other minds reply".
See also Can a machine have a mind? These arguments all have the form "a computer will never do X". Turing offers a selection: Be kind, resourceful, beautiful, friendly, have initiative, have a sense of humour, tell right from wrong, make mistakes, fall in love, enjoy strawberries and cream, make someone fall in love with it, learn from experience, use words properly, be the subject of its own thought, have as much diversity of behaviour as a man, do something really new.
Turing notes that "no support is usually offered for these statements," and that they depend on naive assumptions about how versatile machines may be in the future, or are "disguised forms of the argument from consciousness.
He notes it's easy to program a machine to appear to make a mistake. A machine cannot be the subject of its own thought or can't be self-aware.
A program which can report on its internal states and processes, in the simple sense of a debugger program, can certainly be written. Turing asserts "a machine can undoubtably be its own subject matter.
He notes that, with enough storage capacity, a computer can behave in an astronomical number of different ways. Lady Lovelace 's Objection: One of the most famous objections states that computers are incapable of originality. This is largely because, according to Ada Lovelace , machines are incapable of independent learning.
The Analytical Engine has no pretensions whatever to originate anything. It can do whatever we know how to order it to perform. It can follow analysis; but it has no power of anticipating any analytical relations or truths.
Turing suggests that Lovelace's objection can be reduced to the assertion that computers "can never take us by surprise" and argues that, to the contrary, computers could still surprise humans, in particular where the consequences of different facts are not immediately recognizable.
Turing also argues that Lady Lovelace was hampered by the context from which she wrote, and if exposed to more contemporary scientific knowledge, it would become evident that the brain's storage is quite similar to that of a computer.
Argument from continuity in the nervous system: Modern neurological research has shown that the brain is not digital. Even though neurons fire in an all-or-nothing pulse, both the exact timing of the pulse and the probability of the pulse occurring have analog components. Turing acknowledges this, but argues that any analog system can be simulated to a reasonable degree of accuracy given enough computing power.
Philosopher Hubert Dreyfus would make this argument against "the biological assumption" in Turing replies by stating that this is confusing laws of behaviour with general rules of conduct, and that if on a broad enough scale such as is evident in man machine behaviour would become increasingly difficult to predict.
He argues that, just because we can't immediately see what the laws are, does not mean that no such laws exist. He writes "we certainly know of no circumstances under which we could say, 'we have searched enough.
There are no such laws. Hubert Dreyfus would argue in that human reason and problem solving was not based on formal rules, but instead relied on instincts and awareness that would never be captured in rules.
More recent AI research in robotics and computational intelligence attempts to find the complex rules that govern our "informal" and unconscious skills of perception, mobility and pattern matching. See Dreyfus' critique of AI. Extra-sensory perception : In , extra-sensory perception was an active area of research and Turing chooses to give ESP the benefit of the doubt, arguing that conditions could be created in which mind-reading would not affect the test.
See also: Machine learning In the final section of the paper Turing details his thoughts about the Learning Machine that could play the imitation game successfully.
Therefore, if any digital machine can "act like it is thinking" then, every sufficiently powerful digital machine can. Turing writes, "all digital computers are in a sense equivalent. This allows the original question to be made even more specific.
I.—COMPUTING MACHINERY AND INTELLIGENCE
Turing now restates the original question as "Let us fix our attention on one particular digital computer C. Is it true that by modifying this computer to have an adequate storage, suitably increasing its speed of action, and providing it with an appropriate programme, C can be made to play satisfactorily the part of A in the imitation game, the part of B being taken by a man?
Hence Turing states that the focus is not on "whether all digital computers would do well in the game nor whether the computers that are presently available would do well, but whether there are imaginable computers which would do well". Having clarified the question, Turing turned to answering it: Be kind, resourceful, beautiful, friendly, have initiative, have a sense of humour, tell right from wrong, make mistakes, fall in love, enjoy strawberries and cream, make someone fall in love with it, learn from experience, use words properly, be the subject of its own thought, have as much diversity of behaviour as a man, do something really new.
The Analytical Engine has no pretensions whatever to originate anything. It can do whatever we know how to order it to perform. It can follow analysis; but it has no power of anticipating any analytical relations or truths. In the final section of the paper Turing details his thoughts about the Learning Machine that could play the imitation game successfully. Here Turing first returns to Lady Lovelace's objection that the machine can only do what we tell it to do and he likens it to a situation where a man "injects" an idea into the machine to which the machine responds and then falls off into quiescence.
He extends on this thought by an analogy to an atomic pile of less than critical size which is to be considered the machine and an injected idea is to correspond to a neutron entering the pile from outside the pile; the neutron will cause a certain disturbance which eventually dies away. Turing then builds on that analogy and mentions that if the size of the pile were to be sufficiently large then a neutron entering the pile would cause a disturbance that would continue to increase until the whole pile were destroyed, the pile would be supercritical.
Turing then asks the question as to whether this analogy of a super critical pile could be extended to a human mind and then to a machine. He concludes that such an analogy would indeed be suitable for the human mind with "There does seem to be one for the human mind.
The majority of them seem to be "subcritical," i.
An idea presented to such a mind will on average give rise to less than one idea in reply. A smallish proportion are supercritical.
An idea presented to such a mind that may give rise to a whole "theory" consisting of secondary, tertiary and more remote ideas".
He finally asks if a machine could be made to be supercritical. Turing then mentions that the task of being able to create a machine that could play the imitation game is one of programming and he postulates that by the end of the century it will indeed be technologically possible to program a machine to play the game.
He then mentions that in the process of trying to imitate an adult human mind it becomes important to consider the processes that lead to the adult mind being in its present state; which he summarizes as:.
Given this process he asks whether it would be more appropriate to program a child's mind instead of an adults mind and then subject the child mind to a period of education. He likens the child to a newly bought notebook and speculates that due to its simplicity it would be more easily programmed.
The problem then is broken down into two parts, the programming of a child mind and its education process. He mentions that a child mind would not be expected as desired by the experimenter programmer at the first attempt.
Computing Machinery and Intelligence
A learning process that involves a method of reward and punishment must be in place that will select desirable patterns in the mind. This whole process, Turing mentions, to a large extent is similar to that of evolution by natural selection where the similarities are:. Turing concludes by speculating about a time when machines will compete with humans on numerous intellectual tasks and suggests tasks that could be used to make that start. Turing then suggests that abstract tasks such as playing chess could be a good place to start another method which he puts as "..
An examination of the development in artificial intelligence that has followed reveals that the learning machine did take the abstract path suggested by Turing as in the case of Deep Blue , a chess playing computer developed by IBM and one which defeated the world champion Garry Kasparov though, this too is controversial and the numerous computer chess games which can outplay most amateurs.
From Wikipedia, the free encyclopedia. Main article: Turing test. See also: Turing machine and Church—Turing thesis.Turing consists of 4 volumes: Volume 1: Mechanical Intelligence, D.
Thus, as expressed by Ince , he predicted neural networks. If the computer wins, it must be credited with intelligence.
Turing also notes that we need to determine which "machines" we wish to consider.
Estimatesof the storagecapacity of the brain vary from to binarydigits.
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