Computing Machinery and Intelligence

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Computing Machinery and Intelligence, written by Alan Turing and published in 1950 in Mind, is a seminal paper on the topic of artificial intelligence in which the concept of what is now known as the Turing test was introduced to a wide audience.

Turing's paper considers the question "Can machines think?" Since the words "think" and "machine" can't be defined in clear way that satisfies everyone, Turing suggests we "replace the question by another, which is closely related to it and is expressed in relatively unambiguous words."^[1] To do this, he must first find a simple and unambiguous idea to replace the word "think", second he must explain exactly which "machines" he is considering, and finally, armed with these tools, he formulates a new question, related to the first, that he believes he can answer in the affirmative.

[edit] Turing's test

The "standard interpretation" of the Turing Test, in which player C, the interrogator, is tasked with trying to determine which player - A or B - is a computer and which is a human.

Main article: Turing test

Rather than trying to determine if a machine is thinking, Turing suggests we should ask if the machine can win a game, called the "Imitation Game". It involves three participants in isolated rooms: a computer (which is being tested), a human, and a (human) judge. The human judge can converse with both the human and the computer by typing into a terminal. Both the computer and human try to convince the judge that they are the human. If the judge cannot consistently tell which is which, then the computer wins the game.

Turing writes '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?'"^[2]

As Stevan Harnad notes, the question has become "Can machines do what we (as thinking entities) can do?"^[3] In other words, Turing is no longer asking if a machine can think, he asking if a machine can act like it is thinking. This question avoids the difficult philosophical problem of defining the verb "to think."

[edit] Digital machines

See also: Turing machine and Church-Turing thesis

Turing also notes that we need to determine which "machines" we wish to consider. He points out that a clone, while man-made, would not provide a very interesting example. Turing suggests 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 1950.

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.) Therefor, 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."^[4]

This allows the original question to made even more specific. 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?"^[4] This question, he believes, can be answered without resorting to speculation or philosophy. It has become a straightforward question of software engineering.

[edit] Nine common objections

Having clarified the question, Turing now turned to answering it. He considered these nine common objections, which include all the major arguments against artificial intelligence that have been raised in the years since his paper was first published.^[5]

1. Theological Objection: This states that thinking is a function of man's immortal soul and therefore a machine could not think. Turing writes "In attempting to construct such machines we should not be irreverently usurping His power of creating souls, any more than we are in the procreation of children: rather we are, in either case, instruments of His will providing mansions for the souls that he creates."
2. 'Heads in the Sand' Objection: "The consequences of machines thinking would be too dreadful. 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.
3. Mathematical Objections: This objection uses mathematical theorems, such as Gödel's incompleteness theorem, to show that there are limits to what questions a computer system based on logic can answer. 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 1961 and physicist Roger Penrose in 1989.)^[6]
4. Argument From Consciousness: This argument, suggested by Professor Geoffrey Jefferson in his 1949 Lister Oration states that "not until a machine can write a sonnet or compose a concerto because of thoughts and emotions felt, and not by the chance fall of symbols, could we agree that machine equals brain."^[7] Turing replies by saying that we have no way of knowing that any individual other than ourselves experiences emotions, and that therefore we should accept the test and adds "I do not wish to give the impression that I think there is no mystery about consciousness ... [b]ut I do not think these mysteries necessarily need to be solved before we can answer the question [of whether machines can think]." (This argument, that a computer can't have conscious experiences or understanding would be made 1980 by philosopher John Searle in his Chinese Room argument. Turing's reply is now known as the "other minds reply". See also Can a machine have a mind? in the philosophy of AI.)^[8]
5. Arguments from various disabilities. 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 some one 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 chooses to answer a few of them:
   1. Machines cannot make mistakes. He notes it's easy to program a machine to appear to make a mistake.
   2. 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."
   3. A machine cannot have much diversity of behaviour. He notes that, with enough storage capacity, a computer can behave in an astronomical number of different ways.
6. 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. Turing contradicts this by arguing that Lady Lovelace's assumption was affected 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. Turing further replies that computers could still surprise humans, in particular where the consequences of different facts are not immediately recognizable.
7. 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 1972.)^[9]
8. Argument from the informality of behaviour: This argument states that any system governed by laws will be predictable and therefore not truly intelligent. 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 1972 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.)^[10]
9. Extra-sensory perception: In 1950, extra-sensory perception was an active area and 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.

[edit] Learning machines

Please help improve this article or section by expanding it. Further information might be found on the talk page or at requests for expansion. (June 2008)

[edit] External links

• Full text of the paper
• Full text of the paper
• Stevan Harnad (2004) The Annotation Game: On Turing (1950) on Computing, Machinery, and Intelligence, in Epstein, Robert and Peters, Grace, Eds. The Turing Test Sourcebook: Philosophical and Methodological Issues in the Quest for the Thinking Computer. Kluwer.

[edit] Notes

[edit] References

• Brooks, Rodney (1990), “Elephants Don't Play Chess”, Robotics and Autonomous Systems 6: 3-15, <http://people.csail.mit.edu/brooks/papers/elephants.pdf>. Retrieved on 30 August 2007 
• Crevier, Daniel (1993), AI: The Tumultuous Search for Artificial Intelligence, New York, NY: BasicBooks, ISBN 0-465-02997-3 
• Dreyfus, Hubert (1972), What Computers Can't Do, New York: MIT Press, ISBN 0060110821 
• Dreyfus, Hubert & Dreyfus, Stuart (1986), Mind over Machine: The Power of Human Intuition and Expertise in the Era of the Computer, Oxford, UK: Blackwell 
• Dreyfus, Hubert (1979), What Computers Still Can't Do, New York: MIT Press .
• Haugeland, John (1985), Artificial Intelligence: The Very Idea, MIT Press .
• Moravec, Hans (1976), The Role of Raw Power in Intelligence, <http://www.frc.ri.cmu.edu/users/hpm/project.archive/general.articles/1975/Raw.Power.html> 
• Russell, Stuart J. & Norvig, Peter (2003), Artificial Intelligence: A Modern Approach (2nd ed.), Upper Saddle River, NJ: Prentice Hall, ISBN 0-13-790395-2, <http://aima.cs.berkeley.edu/> 
• Searle, John (1980), “Minds, Brains and Programs”, Behavioral and Brain Sciences 3 (3): 417-457, <http://members.aol.com/NeoNoetics/MindsBrainsPrograms.html> 
• Turing, Alan (October 1950), “Computing Machinery and Intelligence”, Mind LIX (236): 433-460, ISSN 0026-4423, doi:10.1093/mind/LIX.236.433, <http://loebner.net/Prizef/TuringArticle.html>