"Computing Machinery and Intelligence" is a seminal paper written by Alan Turing on the topic of artificial intelligence. The paper, published in 1950 in Mind, was the first to introduce his concept of what is now known as the Turing test to the general public.
Turing's paper considers the question "Can machines think?" Turing says that since the words "think" and "machine" cannot be clearly defined, we should "replace the question by another, which is closely related to it and is expressed in relatively unambiguous words." 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.
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". The original Imitation game, that Turing described, is a simple party game involving three players. Player A is a man, player B is a woman and player C (who plays the role of the interrogator) can be of either sex. In the Imitation Game, player C is unable to see either player A or player B (and knows them only as X and Y), and can communicate with them only through written notes or any other form that does not give away any details about their gender. By asking questions of player A and player B, player C tries to determine which of the two is the man and which is the woman. Player A's role is to trick the interrogator into making the wrong decision, while player B attempts to assist the interrogator in making the right one. Turing proposes a variation of this game that involves the computer: 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?. So the modified game becomes one that 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.[1]
Researchers in the United Kingdom had been exploring "machine intelligence" for up to ten years prior to the founding of the field of artificial intelligence (AI) research in 1956.[2] It was a common topic among the members of the Ratio Club, an informal group of British cybernetics and electronics researchers that included Alan Turing. Turing, in particular, had been running the notion of machine intelligence since at least 1941 and one of the earliest-known mentions of "computer intelligence" was made by him in 1947.[3]
As Stevan Harnad notes, the question has become "Can machines do what we (as thinking entities) can do?" In other words, Turing is no longer asking whether a machine can "think"; he is asking whether a machine can act indistinguishably from the way a thinker acts. This question avoids the difficult philosophical problem of pre-defining the verb "to think" and focuses instead on the performance capacities that being able to think makes possible, and how a causal system can generate them.
Since Turing introduced his test, it has been both highly influential and widely criticised, and has become an important concept in the philosophy of artificial intelligence.[4] Some of its criticisms, such as John Searle's Chinese room, are themselves controversial.[5] Some have taken Turing's question to have been "Can a computer, communicating over a teleprinter, fool a person into believing it is human?"[6] but it seems clear that Turing was not talking about fooling people but about generating human cognitive capacity.
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 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 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.) 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. 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". What is more important is to consider the advancements possible in the state of our machines today regardless of whether we have the available resource to create one or not.
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.[7]
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 chooses to answer a few of them:
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.[12]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.
In 1950, 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. Turing admitted to "overwhelming statistical evidence" for telepathy, likely referring to early 1940s experiments by Samuel Soal, a member of the Society for Psychical Research.
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.
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.e., to correspond in this analogy to piles of sub critical size. 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:
1. The initial state of the mind, say at birth,
2. The education to which it has been subjected,
3. Other experience, not to be described as education, to which it has been subjected.Given this process he asks whether it would be more appropriate to program a child's mind instead of an adult’s 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. 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:
Structure of the child machine = hereditary material
Changes of the child machine = mutations
Natural selection = judgment of the experimenterFollowing this discussion Turing addresses certain specific aspects of the learning machine:
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 "..it is best to provide the machine with the best sense organs that money can buy, and then teach it to understand and speak English.".
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.[14] As for the second suggestion Turing makes, it has been likened by some authors as a call to finding a simulacrum of human cognitive development.[14] Such attempts at finding the underlying algorithms by which children learn the features of the world around them are only beginning to be made.[14] [15] [16]