Turing, A.M. (1950). Computing machinery and intelligence. Mind, 59, 433-460. COMPUTING MACHINERY AND INTELLIGENCE By A. M. Turing 1. The Imitation Game 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 thus: C: Will X please tell me the length of his or her hair? Now suppose X is actually A, then A must answer. It is A's object in the game to try and cause C to make the wrong identification. His answer might therefore be: "My hair is shingled, and the longest strands are about nine inches long." In order that tones of voice may not help the interrogator the answers should be written, or better still, typewritten. The ideal arrangement is to have a teleprinter communicating between the two rooms. Alternatively the question and answers can be repeated by an intermediary. The object of the game for the third player (B) is to help the interrogator. The best strategy for her is probably to give truthful answers. She can add such things as "I am the woman, don't listen to him!" to her answers, but it will avail nothing as the man can make similar remarks. 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?" 2. Critique of the New Problem As well as asking, "What is the answer to this new form of the question," one may ask, "Is this new question a worthy one to investigate?" This latter question we investigate without further ado, thereby cutting short an infinite regress. The new problem has the advantage of drawing a fairly sharp line between the physical and the intellectual capacities of a man. No engineer or chemist claims to be able to produce a material which is indistinguishable from the human skin. It is possible that at some time this might be done, but even supposing this invention available we should feel there was little point in trying to make a "thinking machine" more human by dressing it up in such artificial flesh. The form in which we have set the problem reflects this fact in the condition which prevents the interrogator from seeing or touching the other competitors, or hearing -their voices. Some other advantages of the proposed criterion may be shown up by specimen questions and answers. Thus: Q: Please write me a sonnet on the subject of the Forth Bridge. A : Count me out on this one. I never could write poetry. Q: Add 34957 to 70764. A: (Pause about 30 seconds and then give as answer) 105621. Q: Do you play chess? A: Yes. Q: I have K at my K1, and no other pieces. You have only K at K6 and R at R1. It is your move. What do you play? A: (After a pause of 15 seconds) R-R8 mate. The question and answer method seems to be suitable for introducing almost any one of the fields of human endeavour that we wish to include. We do not wish to penalise the machine for its inability to shine in beauty competitions, nor to penalise a man for losing in a race against an aeroplane. The conditions of our game make these disabilities irrelevant. The "witnesses" can brag, if they consider it advisable, as much as they please about their charms, strength or heroism, but the interrogator cannot demand practical demonstrations. The game may perhaps be criticised on the ground that the odds are weighted too heavily against the machine. If the man were to try and pretend to be the machine he would clearly make a very poor showing. He would be given away at once by slowness and inaccuracy in arithmetic. May not machines carry out something which ought to be described as thinking but which is very different from what a man does? This objection is a very strong one, but at least we can say that if, nevertheless, a machine can be constructed to play the imitation game satisfactorily, we need not be troubled by this objection. It might be urged that when playing the "imitation game" the best strategy for the machine may possibly be something other than imitation of the behaviour of a man. This may be, but I think it is unlikely that there is any great effect of this kind. In any case there is no intention to investigate here the theory of the game, and it will be assumed that the best strategy is to try to provide answers that would naturally be given by a man. 3. The Machines Concerned in the Game The question which we put in 1 will not be quite definite until we have specified what we mean by the word "machine." It is natural that we should wish to permit every kind of engineering technique to be used in our machines. We also wish to allow the possibility than an engineer or team of engineers may construct a machine which works, but whose manner of operation cannot be satisfactorily described by its constructors because they have applied a method which is largely experimental. Finally, we wish to exclude from the machines men born in the usual manner. It is difficult to frame the definitions so as to satisfy these three conditions. One might for instance insist that the team of engineers should be all of one sex, but this would not really be satisfactory, for it is probably possible to rear a complete individual from a single cell of the skin (say) of a man. To do so would be a feat of biological technique deserving of the very highest praise, but we would not be inclined to regard it as a case of "constructing a thinking machine." This prompts us to abandon the requirement that every kind of technique should be permitted. We are the more ready to do so in view of the fact that the present interest in "thinking machines" has been aroused by a particular kind of machine, usually called an "electronic computer" or "digital computer." Following this suggestion we only permit digital computers to take part in our game. This restriction appears at first sight to be a very drastic one. I shall attempt to show that it is not so in reality. To do this necessitates a short account of the nature and properties of these computers. It may also be said that this identification of machines with digital computers, like our criterion for "thinking," will only be unsatisfactory if (contrary to my belief), it turns out that digital computers are unable to give a good showing in the game. There are already a number of digital computers in working order, and it may be asked, "Why not try the experiment straight away? It would be easy to satisfy the conditions of the game. A number of interrogators could be used, and statistics compiled to show how often the right identification was given." The short answer is that we are not asking whether all digital computers would do well in the game nor whether the computers at present available would do well, but whether there are imaginable computers which would do well. But this is only the short answer. We shall see this question in a different light later. 4. Digital Computers The idea behind digital computers may be explained by saying that these machines are intended to carry out any operations which could be done by a human computer. The human computer is supposed to be following fixed rules; he has no authority to deviate from them in any detail. We may suppose that these rules are supplied in a book, which is altered whenever he is put on to a new job. He has also an unlimited supply of paper on which he does his calculations. He may also do his multiplications and additions on a "desk machine," but this is not important. If we use the above explanation as a definition we shall be in danger of circularity of argument. We avoid this by giving an outline. of the means by which the desired effect is achieved. A digital computer can usually be regarded as consisting of three parts: (i) Store. (ii) Executive unit. (iii) Control. The store is a store of information, and corresponds to the human computer's paper, whether this is the paper on which he does his calculations or that on which his book of rules is printed. In so far as the human computer does calculations in his bead a part of the store will correspond to his memory. The executive unit is the part which carries out the various individual operations involved in a calculation. What these individual operations are will vary from machine to machine. Usually fairly lengthy operations can be done such as "Multiply 3540675445 by 7076345687" but in some machines only very simple ones such as "Write down 0" are possible. We have mentioned that the "book of rules" supplied to the computer is replaced in the machine by a part of the store. It is then called the "table of instructions." It is the duty of the control to see that these instructions are obeyed correctly and in the right order. The control is so constructed that this necessarily happens. The information in the store is usually broken up into packets of moderately small size. In one machine, for instance, a packet might consist of ten decimal digits. Numbers are assigned to the parts of the store in which the various packets of information are stored, in some systematic manner. A typical instruction might say- "Add the number stored in position 6809 to that in 4302 and put the result back into the latter storage position." Needless to say it would not occur in the machine expressed in English. It would more likely be coded in a form such as 6809430217. Here 17 says which of various possible operations is to be performed on the two numbers. In this case the)e operation is that described above, viz., "Add the number. . . ." It will be noticed that the instruction takes up 10 digits and so forms one packet of information, very conveniently. The control will normally take the instructions to be obeyed in the order of the positions in which they are stored, but occasionally an instruction such as "Now obey the instruction stored in position 5606, and continue from there" may be encountered, or again "If position 4505 contains 0 obey next the instruction stored in 6707, otherwise continue straight on." Instructions of these latter types are very important because they make it possible for a sequence of operations to be replaced over and over again until some condition is fulfilled, but in doing so to obey, not fresh instructions on each repetition, but the same ones over and over again. To take a domestic analogy. Suppose Mother wants Tommy to call at the cobbler's every morning on his way to school to see if her shoes are done, she can ask him afresh every morning. Alternatively she can stick up a notice once and for all in the hall which he will see when he leaves for school and which tells him to call for the shoes, and also to destroy the notice when he comes back if he has the shoes with him. The reader must accept it as a fact that digital computers can be constructed, and indeed have been constructed, according to the principles we have described, and that they can in fact mimic the actions of a human computer very closely. The book of rules which we have described our human computer as using is of course a convenient fiction. Actual human computers really remember what they have got to do. If one wants to make a machine mimic the behaviour of the human computer in some complex operation one has to ask him how it is done, and then translate the answer into the form of an instruction table. Constructing instruction tables is usually described as "programming." To "programme a machine to carry out the operation A" means to put the appropriate instruction table into the machine so that it will do A. An interesting variant on the idea of a digital computer is a "digital computer with a random element." These have instructions involving the throwing of a die or some equivalent electronic process; one such instruction might for instance be, "Throw the die and put the-resulting number into store 1000." Sometimes such a machine is described as having free will (though I would not use this phrase myself), It is not normally possible to determine from observing a machine whether it has a random element, for a similar effect can be produced by such devices as making the choices depend on the digits of the decimal for . Most actual digital computers have only a finite store. There is no theoretical difficulty in the idea of a computer with an unlimited store. Of course only a finite part can have been used at any one time. Likewise only a finite amount can have been constructed, but we can imagine more and more being added as required. Such computers have special theoretical interest and will be called infinitive capacity computers. The idea of a digital computer is an old one. Charles Babbage, Lucasian Professor of Mathematics at Cambridge from 1828 to 1839, planned such a machine, called the Analytical Engine, but it was never completed. Although Babbage had all the essential ideas, his machine was not at that time such a very attractive prospect. The speed which would have been available would be definitely faster than a human computer but something like I 00 times slower than the Manchester machine, itself one of the slower of the modern machines, The storage was to be purely mechanical, using wheels and cards. The fact that Babbage's Analytical Engine was to be entirely mechanical will help us to rid ourselves of a superstition. Importance is often attached to the fact that modern digital computers are electrical, and that the nervous system also is electrical. Since Babbage's machine was not electrical, and since all digital computers are in a sense equivalent, we see that this use of electricity cannot be of theoretical importance. Of course electricity usually comes in where fast signalling is concerned, so that it is not surprising that we find it in both these connections. In the nervous system chemical phenomena are at least as important as electrical. In certain computers the storage system is mainly acoustic. The feature of using electricity is thus seen to be only a very superficial similarity. If we wish to find such similarities we should took rather for mathematical analogies of function. 5. Universality of Digital Computers The digital computers considered in the last section may be classified amongst the "discrete-state machines." These are the machines which move by sudden jumps or clicks from one quite definite state to another. These states are sufficiently different for the possibility of confusion between them to be ignored. Strictly speaking there, are no such machines. Everything really moves continuously. But there are many kinds of machine which can profitably be thought of as being discrete-state machines. For instance in considering the switches for a lighting system it is a convenient fiction that each switch must be definitely on or definitely off. There must be intermediate positions, but for most purposes we can forget about them. As an example of a discrete-state machine we might consider a wheel which clicks round through 120 once a second, but may be stopped by a ]ever which can be operated from outside; in addition a lamp is to light in one of the positions of the wheel. This machine could be described abstractly as follows. The internal state of the machine (which is described by the position of the wheel) may be q1, q2 or q3. There is an input signal i0. or i1 (position of ]ever). The internal state at any moment is determined by the last state and input signal according to the table (TABLE DELETED) The output signals, the only externally visible indication of the internal state (the light) are described by the table State q1 q2 q3 output o0 o0 o1 This example is typical of discrete-state machines. They can be described by such tables provided they have only a finite number of possible states. It will seem that given the initial state of the machine and the input signals it is always possible to predict all future states, This is reminiscent of Laplace's view that from the complete state of the universe at one moment of time, as described by the positions and velocities of all particles, it should be possible to predict all future states. The prediction which we are considering is, however, rather nearer to practicability than that considered by Laplace. The system of the "universe as a whole" is such that quite small errors in the initial conditions can have an overwhelming effect at a later time. The displacement of a single electron by a billionth of a centimetre at one moment might make the difference between a man being killed by an avalanche a year later, or escaping. It is an essential property of the mechanical systems which we have called "discrete-state machines" that this phenomenon does not occur. Even when we consider the actual physical machines instead of the idealised machines, reasonably accurate knowledge of the state at one moment yields reasonably accurate knowledge any number of steps later. As we have mentioned, digital computers fall within the class of discrete-state machines. But the number of states of which such a machine is capable is usually enormously large. For instance, the number for the machine now working at Manchester is about 2 165,000, i.e., about 10 50,000. Compare this with our example of the clicking wheel described above, which had three states. It is not difficult to see why the number of states should be so immense. The computer includes a store corresponding to the paper used by a human computer. It must be possible to write into the store any one of the combinations of symbols which might have been written on the paper. For simplicity suppose that only digits from 0 to 9 are used as symbols. Variations in handwriting are ignored. Suppose the computer is allowed 100 sheets of paper each containing 50 lines each with room for 30 digits. Then the number of states is 10 100x50x30 i.e., 10 150,000 . This is about the number of states of three Manchester machines put together. The logarithm to the base two of the number of states is usually called the "storage capacity" of the machine. Thus the Manchester machine has a storage capacity of about 165,000 and the wheel machine of our example about 1.6. If two machines are put together their capacities must be added to obtain the capacity of the resultant machine. This leads to the possibility of statements such as "The Manchester machine contains 64 magnetic tracks each with a capacity of 2560, eight electronic tubes with a capacity of 1280. Miscellaneous storage amounts to about 300 making a total of 174,380." Given the table corresponding to a discrete-state machine it is possible to predict what it will do. There is no reason why this calculation should not be carried out by means of a digital computer. Provided it could be carried out sufficiently quickly the digital computer could mimic the behavior of any discrete-state machine. The imitation game could then be played with the machine in question (as B) and the mimicking digital computer (as A) and the interrogator would be unable to distinguish them. Of course the digital computer must have an adequate storage capacity as well as working sufficiently fast. Moreover, it must be programmed afresh for each new machine which it is desired to mimic. This special property of digital computers, that they can mimic any discrete-state machine, is described by saying that they are universal machines. The existence of machines with this property has the important consequence that, considerations of speed apart, it is unnecessary to design various new machines to do various computing processes. They can all be done with one digital computer, suitably programmed for each case. It 'ill be seen that as a consequence of this all digital computers are in a sense equivalent. We may now consider again the point raised at the end of §3. It was suggested tentatively that the question, "Can machines think?" should be replaced by "Are there imaginable digital computers which would do well in the imitation game?" If we wish we can make this superficially more general and ask "Are there discrete-state machines which would do well?" But in view of the universality property we see that either of these questions is equivalent to this, "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?" 6. Contrary Views on the Main Question We may now consider the ground to have been cleared and we are ready to proceed to the debate on our question, "Can machines think?" and the variant of it quoted at the end of the last section. We cannot altogether abandon the original form of the problem, for opinions will differ as to the appropriateness of the substitution and we must at least listen to what has to be said in this connexion. It will simplify matters for the reader if I explain first my own beliefs in the matter. Consider first the more accurate form of the question. I believe that in about fifty years' time it will be possible, to programme computers, with a storage capacity of about 109, to make them play the imitation game so well that an average interrogator will not have more than 70 per cent chance of making the right identification after five minutes of questioning. The original question, "Can machines think?" I believe to be too meaningless to deserve discussion. Nevertheless I believe that at the end of the century the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted. I believe further that no useful purpose is served by concealing these beliefs. The popular view that scientists proceed inexorably from well-established fact to well-established fact, never being influenced by any improved conjecture, is quite mistaken. Provided it is made clear which are proved facts and which are conjectures, no harm can result. Conjectures are of great importance since they suggest useful lines of research. I now proceed to consider opinions opposed to my own. (1) The Theological Objection Thinking is a function of man's immortal soul. God has given an immortal soul to every man and woman, but not to any other animal or to machines. Hence no animal or machine can think. I am unable to accept any part of this, but will attempt to reply in theological terms. I should find the argument more convincing if animals were classed with men, for there is a greater difference, to my mind, between the typical animate and the inanimate than there is between man and the other animals. The arbitrary character of the orthodox view becomes clearer if we consider how it might appear to a member of some other religious community. How do Christians regard the Moslem view that women have no souls? But let us leave this point aside and return to the main argument. It appears to me that the argument quoted above implies a serious restriction of the omnipotence of the Almighty. It is admitted that there are certain things that He cannot do such as making one equal to two, but should we not believe that He has freedom to confer a soul on an elephant if He sees fit? We might expect that He would only exercise this power in conjunction with a mutation which provided the elephant with an appropriately improved brain to minister to the needs of this sort[. An argument of exactly similar form may be made for the case of machines. It may seem different because it is more difficult to "swallow." But this really only means that we think it would be less likely that He would consider the circumstances suitable for conferring a soul. The circumstances in question are discussed in the rest of this paper. 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. However, this is mere speculation. I am not very impressed with theological arguments whatever they may be used to support. Such arguments have often been found unsatisfactory in the past. In the time of Galileo it was argued that the texts, "And the sun stood still . . . and hasted not to go down about a whole day" (Joshua x. 13) and "He laid the foundations of the earth, that it should not move at any time" (Psalm cv. 5) were an adequate refutation of the Copernican theory. With our present knowledge such an argument appears futile. When that knowledge was not available it made a quite different impression. (2) The "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 argument is seldom expressed quite so openly as in the form above. But it affects most of us who think about it at all. We like to believe that Man is in some subtle way superior to the rest of creation. It is best if he can be shown to be necessarily superior, for then there is no danger of him losing his commanding position. The popularity of the theological argument is clearly connected with this feeling. It is likely to be quite strong in intellectual people, since they value the power of thinking more highly than others, and are more inclined to base their belief in the superiority of Man on this power. I do not think that this argument is sufficiently substantial to require refutation. Consolation would be more appropriate: perhaps this should be sought in the transmigration of souls. (3) The Mathematical Objection There are a number of results of mathematical logic which can be used to show that there are limitations to the powers of discrete-state machines. The best known of these results is known as Godel's theorem ( 1931 ) and shows that in any sufficiently powerful logical system statements can be formulated which can neither be proved nor disproved within the system, unless possibly the system itself is inconsistent. There are other, in some respects similar, results due to Church (1936), Kleene (1935), Rosser, and Turing (1937). The latter result is the most convenient to consider, since it refers directly to machines, whereas the others can only be used in a comparatively indirect argument: for instance if Godel's theorem is to be used we need in addition to have some means of describing logical systems in terms of machines, and machines in terms of logical systems. The result in question refers to a type of machine which is essentially a digital computer with an infinite capacity. It states that there are certain things that such a machine cannot do. If it is rigged up to give answers to questions as in the imitation game, there will be some questions to which it will either give a wrong answer, or fail to give an answer at all however much time is allowed for a reply. There may, of course, be many such questions, and questions which cannot be answered by one machine may be satisfactorily answered by another. We are of course supposing for the present that the questions are of the kind to which an answer "Yes" or "No" is appropriate, rather than questions such as "What do you think of Picasso?" The questions that we know the machines must fail on are of this type, "Consider the machine specified as follows. . . . Will this machine ever answer 'Yes' to any question?" The dots are to be replaced by a description of some machine in a standard form, which could be something like that used in §5. When the machine described bears a certain comparatively simple relation to the machine which is under interrogation, it can be shown that the answer is either wrong or not forthcoming. This is the mathematical result: it is argued that it proves a disability of machines to which the human intellect is not subject. The short answer to this argument is that although it is established that there are limitations to the Powers If any particular machine, it has only been stated, without any sort of proof, that no such limitations apply to the human intellect. But I do not think this view can be dismissed quite so lightly. Whenever one of these machines is asked the appropriate critical question, and gives a definite answer, we know that this answer must be wrong, and this gives us a certain feeling of superiority. Is this feeling illusory? It is no doubt quite genuine, but I do not think too much importance should be attached to it. We too often give wrong answers to questions ourselves to be justified in being very pleased at such evidence of fallibility on the part of the machines. Further, our superiority can only be felt on such an occasion in relation to the one machine over which we have scored our petty triumph. There would be no question of triumphing simultaneously over all machines. In short, then, there might be men cleverer than any given machine, but then again there might be other machines cleverer again, and so on. Those who hold to the mathematical argument would, I think, mostly he willing to accept the imitation game as a basis for discussion, Those who believe in the two previous objections would probably not be interested in any criteria. (4) The Argument from Consciousness This argument is very, well expressed in Professor Jefferson's Lister Oration for 1949, from which I quote. "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-that is, not only write it but know that it had written it. No mechanism could feel (and not merely artificially signal, an easy contrivance) pleasure at its successes, grief when its valves fuse, be warmed by flattery, be made miserable by its mistakes, be charmed by sex, be angry or depressed when it cannot get what it wants." This argument appears to be a denial of the validity of our test. According to the most extreme form of this view the only way by which one could be sure that machine thinks is to be the machine and to feel oneself thinking. One could then describe these feelings to the world, but of course no one would be justified in taking any notice. Likewise according to this view the only way to know that a man thinks is to be that particular man. It is in fact the solipsist point of view. It may be the most logical view to hold but it makes communication of ideas difficult. A is liable to believe "A thinks but B does not" whilst B believes "B thinks but A does not." instead of arguing continually over this point it is usual to have the polite convention that everyone thinks. I am sure that Professor Jefferson does not wish to adopt the extreme and solipsist point of view. Probably he would be quite willing to accept the imitation game as a test. The game (with the player B omitted) is frequently used in practice under the name of viva voce to discover whether some one really understands something or has "learnt it parrot fashion." Let us listen in to a part of such a viva voce: Interrogator: In the first line of your sonnet which reads "Shall I compare thee to a summer's day," would not "a spring day" do as well or better? Witness: It wouldn't scan. Interrogator: How about "a winter's day," That would scan all right. Witness: Yes, but nobody wants to be compared to a winter's day. Interrogator: Would you say Mr. Pickwick reminded you of Christmas? Witness: In a way. Interrogator: Yet Christmas is a winter's day, and I do not think Mr. Pickwick would mind the comparison. Witness: I don't think you're serious. By a winter's day one means a typical winter's day, rather than a special one like Christmas. And so on, What would Professor Jefferson say if the sonnet-writing machine was able to answer like this in the viva voce? I do not know whether he would regard the machine as "merely artificially signalling" these answers, but if the answers were as satisfactory and sustained as in the above passage I do not think he would describe it as "an easy contrivance." This phrase is, I think, intended to cover such devices as the inclusion in the machine of a record of someone reading a sonnet, with appropriate switching to turn it on from time to time. In short then, I think that most of those who support the argument from consciousness could be persuaded to abandon it rather than be forced into the solipsist position. They will then probably be willing to accept our test. I do not wish to give the impression that I think there is no mystery about consciousness. There is, for instance, something of a paradox connected with any attempt to localise it. But I do not think these mysteries necessarily need to be solved before we can answer the question with which we are concerned in this paper. (5) Arguments from Various Disabilities These arguments take the form, "I grant you that you can make machines do all the things you have mentioned but you will never be able to make one to do X." Numerous features X are suggested in this connexion I offer 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. No support is usually offered for these statements. I believe they are mostly founded on the principle of scientific induction. A man has seen thousands of machines in his lifetime. From what he sees of them he draws a number of general conclusions. They are ugly, each is designed for a very limited purpose, when required for a minutely different purpose they are useless, the variety of behaviour of any one of them is very small, etc., etc. Naturally he concludes that these are necessary properties of machines in general. Many of these limitations are associated with the very small storage capacity of most machines. (I am assuming that the idea of storage capacity is extended in some way to cover machines other than discrete-state machines. The exact definition does not matter as no mathematical accuracy is claimed in the present discussion,) A few years ago, when very little had been heard of digital computers, it was possible to elicit much incredulity concerning them, if one mentioned their properties without describing their construction. That was presumably due to a similar application of the principle of scientific induction. These applications of the principle are of course largely unconscious. When a burnt child fears the fire and shows that he fears it by avoiding it, f should say that he was applying scientific induction. (I could of course also describe his behaviour in many other ways.) The works and customs of mankind do not seem to be very suitable material to which to apply scientific induction. A very large part of space-time must be investigated, if reliable results are to be obtained. Otherwise we may (as most English 'Children do) decide that everybody speaks English, and that it is silly to learn French. There are, however, special remarks to be made about many of the disabilities that have been mentioned. The inability to enjoy strawberries and cream may have struck the reader as frivolous. Possibly a machine might be made to enjoy this delicious dish, but any attempt to make one do so would be idiotic. What is important about this disability is that it contributes to some of the other disabilities, e.g., to the difficulty of the same kind of friendliness occurring between man and machine as between white man and white man, or between black man and black man. The claim that "machines cannot make mistakes" seems a curious one. One is tempted to retort, "Are they any the worse for that?" But let us adopt a more sympathetic attitude, and try to see what is really meant. I think this criticism can be explained in terms of the imitation game. It is claimed that the interrogator could distinguish the machine from the man simply by setting them a number of problems in arithmetic. The machine would be unmasked because of its deadly accuracy. The reply to this is simple. The machine (programmed for playing the game) would not attempt to give the right answers to the arithmetic problems. It would deliberately introduce mistakes in a manner calculated to confuse the interrogator. A mechanical fault would probably show itself through an unsuitable decision as to what sort of a mistake to make in the arithmetic. Even this interpretation of the criticism is not sufficiently sympathetic. But we cannot afford the space to go into it much further. It seems to me that this criticism depends on a confusion between two kinds of mistake, We may call them "errors of functioning" and "errors of conclusion." Errors of functioning are due to some mechanical or electrical fault which causes the machine to behave otherwise than it was designed to do. In philosophical discussions one likes to ignore the possibility of such errors; one is therefore discussing "abstract machines." These abstract machines are mathematical fictions rather than physical objects. By definition they are incapable of errors of functioning. In this sense we can truly say that "machines can never make mistakes." Errors of conclusion can only arise when some meaning is attached to the output signals from the machine. The machine might, for instance, type out mathematical equations, or sentences in English. When a false proposition is typed we say that the machine has committed an error of conclusion. There is clearly no reason at all for saying that a machine cannot make this kind of mistake. It might do nothing but type out repeatedly "O = I." To take a less perverse example, it might have some method for drawing conclusions by scientific induction. We must expect such a method to lead occasionally to erroneous results. The claim that a machine cannot be the subject of its own thought can of course only be answered if it can be shown that the machine has some thought with some subject matter. Nevertheless, "the subject matter of a machine's operations" does seem to mean something, at least to the people who deal with it. If, for instance, the machine was trying to find a solution of the equation x2 - 40x - 11 = 0 one would be tempted to describe this equation as part of the machine's subject matter at that moment. In this sort of sense a machine undoubtedly can be its own subject matter. It may be used to help in making up its own programmes, or to predict the effect of alterations in its own structure. By observing the results of its own behaviour it can modify its own programmes so as to achieve some purpose more effectively. These are possibilities of the near future, rather than Utopian dreams. The criticism that a machine cannot have much diversity of behaviour is just a way of saying that it cannot have much storage capacity. Until fairly recently a storage capacity of even a thousand digits was very rare. The criticisms that we are considering here are often disguised forms of the argument from consciousness, Usually if one maintains that a machine can do one of these things, and describes the kind of method that the machine could use, one will not make much of an impression. It is thought that tile method (whatever it may be, for it must be mechanical) is really rather base. Compare the parentheses in Jefferson's statement quoted on page 22. (6) Lady Lovelace's Objection Our most detailed information of Babbage's Analytical Engine comes from a memoir by Lady Lovelace ( 1842). In it she states, "The Analytical Engine has no pretensions to originate anything. It can do whatever we know how to order it to perform" (her italics). This statement is quoted by Hartree ( 1949) who adds: "This does not imply that it may not be possible to construct electronic equipment which will 'think for itself,' or in which, in biological terms, one could set up a conditioned reflex, which would serve as a basis for 'learning.' Whether this is possible in principle or not is a stimulating and exciting question, suggested by some of these recent developments But it did not seem that the machines constructed or projected at the time had this property." I am in thorough agreement with Hartree over this. It will be noticed that he does not assert that the machines in question had not got the property, but rather that the evidence available to Lady Lovelace did not encourage her to believe that they had it. It is quite possible that the machines in question had in a sense got this property. For suppose that some discrete-state machine has the property. The Analytical Engine was a universal digital computer, so that, if its storage capacity and speed were adequate, it could by suitable programming be made to mimic the machine in question. Probably this argument did not occur to the Countess or to Babbage. In any case there was no obligation on them to claim all that could be claimed. This whole question will be considered again under the heading of learning machines. A variant of Lady Lovelace's objection states that a machine can "never do anything really new." This may be parried for a moment with the saw, "There is nothing new under the sun." Who can be certain that "original work" that he has done was not simply the growth of the seed planted in him by teaching, or the effect of following well-known general principles. A better variant of the objection says that a machine can never "take us by surprise." This statement is a more direct challenge and can be met directly. Machines take me by surprise with great frequency. This is largely because I do not do sufficient calculation to decide what to expect them to do, or rather because, although I do a calculation, I do it in a hurried, slipshod fashion, taking risks. Perhaps I say to myself, "I suppose the Voltage here ought to he the same as there: anyway let's assume it is." Naturally I am often wrong, and the result is a surprise for me for by the time the experiment is done these assumptions have been forgotten. These admissions lay me open to lectures on the subject of my vicious ways, but do not throw any doubt on my credibility when I testify to the surprises I experience. I do not expect this reply to silence my critic. He will probably say that h surprises are due to some creative mental act on my part, and reflect no credit on the machine. This leads us back to the argument from consciousness, and far from the idea of surprise. It is a line of argument we must consider closed, but it is perhaps worth remarking that the appreciation of something as surprising requires as much of a "creative mental act" whether the surprising event originates from a man, a book, a machine or anything else. The view that machines cannot give rise to surprises is due, I believe, to a fallacy to which philosophers and mathematicians are particularly subject. This is the assumption that as soon as a fact is presented to a mind all consequences of that fact spring into the mind simultaneously with it. It is a very useful assumption under many circumstances, but one too easily forgets that it is false. A natural consequence of doing so is that one then assumes that there is no virtue in the mere working out of consequences from data and general principles. (7) Argument from Continuity in the Nervous System The nervous system is certainly not a discrete-state machine. A small error in the information about the size of a nervous impulse impinging on a neuron, may make a large difference to the size of the outgoing impulse. It may be argued that, this being so, one cannot expect to be able to mimic the behaviour of the nervous system with a discrete-state system. It is true that a discrete-state machine must be different from a continuous machine. But if we adhere to the conditions of the imitation game, the interrogator will not be able to take any advantage of this difference. The situation can be made clearer if we consider sonic other simpler continuous machine. A differential analyser will do very well. (A differential analyser is a certain kind of machine not of the discrete-state type used for some kinds of calculation.) Some of these provide their answers in a typed form, and so are suitable for taking part in the game. It would not be possible for a digital computer to predict exactly what answers the differential analyser would give to a problem, but it would be quite capable of giving the right sort of answer. For instance, if asked to give the value of (actually about 3.1416) it would be reasonable to choose at random between the values 3.12, 3.13, 3.14, 3.15, 3.16 with the probabilities of 0.05, 0.15, 0.55, 0.19, 0.06 (say). Under these circumstances it would be very difficult for the interrogator to distinguish the differential analyser from the digital computer. (8) The Argument from Informality of Behaviour It is not possible to produce a set of rules purporting to describe what a man should do in every conceivable set of circumstances. One might for instance have a rule that one is to stop when one sees a red traffic light, and to go if one sees a green one, but what if by some fault both appear together? One may perhaps decide that it is safest to stop. But some further difficulty may well arise from this decision later. To attempt to provide rules of conduct to cover every eventuality, even those arising from traffic lights, appears to be impossible. With all this I agree. From this it is argued that we cannot be machines. I shall try to reproduce the argument, but I fear I shall hardly do it justice. It seems to run something like this. "if each man had a definite set of rules of conduct by which he regulated his life he would be no better than a machine. But there are no such rules, so men cannot be machines." The undistributed middle is glaring. I do not think the argument is ever put quite like this, but I believe this is the argument used nevertheless. There may however be a certain confusion between "rules of conduct" and "laws of behaviour" to cloud the issue. By "rules of conduct" I mean precepts such as "Stop if you see red lights," on which one can act, and of which one can be conscious. By "laws of behaviour" I mean laws of nature as applied to a man's body such as "if you pinch him he will squeak." If we substitute "laws of behaviour which regulate his life" for "laws of conduct by which he regulates his life" in the argument quoted the undistributed middle is no longer insuperable. For we believe that it is not only true that being regulated by laws of behaviour implies being some sort of machine (though not necessarily a discrete-state machine), but that conversely being such a machine implies being regulated by such laws. However, we cannot so easily convince ourselves of the absence of complete laws of behaviour as of complete rules of conduct. The only way we know of for finding such laws is scientific observation, and we certainly know of no circumstances under which we could say, "We have searched enough. There are no such laws." We can demonstrate more forcibly that any such statement would be unjustified. For suppose we could be sure of finding such laws if they existed. Then given a discrete-state machine it should certainly be possible to discover by observation sufficient about it to predict its future behaviour, and this within a reasonable time, say a thousand years. But this does not seem to be the case. I have set up on the Manchester computer a small programme using only 1,000 units of storage, whereby the machine supplied with one sixteen-figure number replies with another within two seconds. I would defy anyone to learn from these replies sufficient about the programme to be able to predict any replies to untried values. (9) The Argument from Extrasensory Perception I assume that the reader is familiar with the idea of extrasensory perception, and the meaning of the four items of it, viz., telepathy, clairvoyance, precognition and psychokinesis. These disturbing phenomena seem to deny all our usual scientific ideas. How we should like to discredit them! Unfortunately the statistical evidence, at least for telepathy, is overwhelming. It is very difficult to rearrange one's ideas so as to fit these new facts in. Once one has accepted them it does not seem a very big step to believe in ghosts and bogies. The idea that our bodies move simply according to the known laws of physics, together with some others not yet discovered but somewhat similar, would be one of the first to go. This argument is to my mind quite a strong one. One can say in reply that many scientific theories seem to remain workable in practice, in spite of clashing with ESP; that in fact one can get along very nicely if one forgets about it. This is rather cold comfort, and one fears that thinking is just the kind of phenomenon where ESP may be especially relevant. A more specific argument based on ESP might run as follows: "Let us play the imitation game, using as witnesses a man who is good as a telepathic receiver, and a digital computer. The interrogator can ask such questions as 'What suit does the card in my right hand belong to?' The man by telepathy or clairvoyance gives the right answer 130 times out of 400 cards. The machine can only guess at random, and perhaps gets 104 right, so the interrogator makes the right identification." There is an interesting possibility which opens here. Suppose the digital computer contains a random number generator. Then it will be natural to use this to decide what answer to give. But then the random number generator will be subject to the psychokinetic powers of the interrogator. Perhaps this psychokinesis might cause the machine to guess right more often than would be expected on a probability calculation, so that the interrogator might still be unable to make the right identification. On the other hand, he might be able to guess right without any questioning, by clairvoyance. With ESP anything may happen. If telepathy is admitted it will be necessary to tighten our test up. The situation could be regarded as analogous to that which would occur if the interrogator were talking to himself and one of the competitors was listening with his ear to the wall. To put the competitors into a "telepathy-proof room" would satisfy all requirements. 7. Learning Machines The reader will have anticipated that I have no very convincing arguments of a positive nature to support my views. If I had I should not have taken such pains to point out the fallacies in contrary views. Such evidence as I have I shall now give. Let us return for a moment to Lady Lovelace's objection, which stated that the machine can only do what we tell it to do. One could say that a man can "inject" an idea into the machine, and that it will respond to a certain extent and then drop into quiescence, like a piano string struck by a hammer. Another simile would be an atomic pile of less than critical size: an injected idea is to correspond to a neutron entering the pile from without. Each such neutron will cause a certain disturbance which eventually dies away. If, however, the size of the pile is sufficiently increased, tire disturbance caused by such an incoming neutron will very likely go on and on increasing until the whole pile is destroyed. Is there a corresponding phenomenon for minds, and is there one for machines? 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 subcritical 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. Animals minds seem to be very definitely subcritical. Adhering to this analogy we ask, "Can a machine be made to be supercritical?" The "skin-of-an-onion" analogy is also helpful. In considering the functions of the mind or the brain we find certain operations which we can explain in purely mechanical terms. This we say does not correspond to the real mind: it is a sort of skin which we must strip off if we are to find the real mind. But then in what remains we find a further skin to be stripped off, and so on. Proceeding in this way do we ever come to the "real" mind, or do we eventually come to the skin which has nothing in it? In the latter case the whole mind is mechanical. (It would not be a discrete-state machine however. We have discussed this.) These last two paragraphs do not claim to be convincing arguments. They should rather be described as "recitations tending to produce belief." The only really satisfactory support that can be given for the view expressed at the beginning of §6, will be that provided by waiting for the end of the century and then doing the experiment described. But what can we say in the meantime? What steps should be taken now if the experiment is to be successful? As I have explained, the problem is mainly one of programming. Advances in engineering will have to be made too, but it seems unlikely that these will not be adequate for the requirements. Estimates of the storage capacity of the brain vary from 1010 to 1015 binary digits. I incline to the lower values and believe that only a very small fraction is used for the higher types of thinking. Most of it is probably used for the retention of visual impressions, I should be surprised if more than 109 was required for satisfactory playing of the imitation game, at any rate against a blind man. (Note: The capacity of the Encyclopaedia Britannica, 11th edition, is 2 X 109) A storage capacity of 107, would be a very practicable possibility even by present techniques. It is probably not necessary to increase the speed of operations of the machines at all. Parts of modern machines which can be regarded as analogs of nerve cells work about a thousand times faster than the latter. This should provide a "margin of safety" which could cover losses of speed arising in many ways, Our problem then is to find out how to programme these machines to play the game. At my present rate of working I produce about a thousand digits of progratiirne a day, so that about sixty workers, working steadily through the fifty years might accomplish the job, if nothing went into the wastepaper basket. Some more expeditious method seems desirable. In the process of trying to imitate an adult human mind we are bound to think a good deal about the process which has brought it to the state that it is in. We may notice three components. (a) The initial state of the mind, say at birth, (b) The education to which it has been subjected, (c) Other experience, not to be described as education, to which it has been subjected. Instead of trying to produce a programme to simulate the adult mind, why not rather try to produce one which simulates the child's? If this were then subjected to an appropriate course of education one would obtain the adult brain. Presumably the child brain is something like a notebook as one buys it from the stationer's. Rather little mechanism, and lots of blank sheets. (Mechanism and writing are from our point of view almost synonymous.) Our hope is that there is so little mechanism in the child brain that something like it can be easily programmed. The amount of work in the education we can assume, as a first approximation, to be much the same as for the human child. We have thus divided our problem into two parts. The child programme and the education process. These two remain very closely connected. We cannot expect to find a good child machine at the first attempt. One must experiment with teaching one such machine and see how well it learns. One can then try another and see if it is better or worse. There is an obvious connection between this process and evolution, by the identifications Structure of the child machine = hereditary material Changes of the child machine = mutation, Natural selection = judgment of the experimenter One may hope, however, that this process will be more expeditious than evolution. The survival of the fittest is a slow method for measuring advantages. The experimenter, by the exercise of intelligence, should he able to speed it up. Equally important is the fact that he is not restricted to random mutations. If he can trace a cause for some weakness he can probably think of the kind of mutation which will improve it. It will not be possible to apply exactly the same teaching process to the machine as to a normal child. It will not, for instance, be provided with legs, so that it could not be asked to go out and fill the coal scuttle. Possibly it might not have eyes. But however well these deficiencies might be overcome by clever engineering, one could not send the creature to school without the other children making excessive fun of it. It must be given some tuition. We need not be too concerned about the legs, eyes, etc. The example of Miss Helen Keller shows that education can take place provided that communication in both directions between teacher and pupil can take place by some means or other. We normally associate punishments and rewards with the teaching process. Some simple child machines can be constructed or programmed on this sort of principle. The machine has to be so constructed that events which shortly preceded the occurrence of a punishment signal are unlikely to be repeated, whereas a reward signal increased the probability of repetition of the events which led up to it. These definitions do not presuppose any feelings on the part of the machine, I have done some experiments with one such child machine, and succeeded in teaching it a few things, but the teaching method was too unorthodox for the experiment to be considered really successful. The use of punishments and rewards can at best be a part of the teaching process. Roughly speaking, if the teacher has no other means of communicating to the pupil, the amount of information which can reach him does not exceed the total number of rewards and punishments applied. By the time a child has learnt to repeat "Casabianca" he would probably feel very sore indeed, if the text could only be discovered by a "Twenty Questions" technique, every "NO" taking the form of a blow. It is necessary therefore to have some other "unemotional" channels of communication. If these are available it is possible to teach a machine by punishments and rewards to obey orders given in some language, e.g., a symbolic language. These orders are to be transmitted through the "unemotional" channels. The use of this language will diminish greatly the number of punishments and rewards required. Opinions may vary as to the complexity which is suitable in the child machine. One might try to make it as simple as possible consistently with the general principles. Alternatively one might have a complete system of logical inference "built in."' In the latter case the store would be largely occupied with definitions and propositions. The propositions would have various kinds of status, e.g., well-established facts, conjectures, mathematically proved theorems, statements given by an authority, expressions having the logical form of proposition but not belief-value. Certain propositions may be described as "imperatives." The machine should be so constructed that as soon as an imperative is classed as "well established" the appropriate action automatically takes place. To illustrate this, suppose the teacher says to the machine, "Do your homework now." This may cause "Teacher says 'Do your homework now' " to be included amongst the well-established facts. Another such fact might be, "Everything that teacher says is true." Combining these may eventually lead to the imperative, "Do your homework now," being included amongst the well-established facts, and this, by the construction of the machine, will mean that the homework actually gets started, but the effect is very satisfactory. The processes of inference used by the machine need not be such as would satisfy the most exacting logicians. There might for instance be no hierarchy of types. But this need not mean that type fallacies will occur, any more than we are bound to fall over unfenced cliffs. Suitable imperatives (expressed within the systems, not forming part of the rules of the system) such as "Do not use a class unless it is a subclass of one which has been mentioned by teacher" can have a similar effect to "Do not go too near the edge." The imperatives that can be obeyed by a machine that has no limbs are bound to be of a rather intellectual character, as in the example (doing homework) given above. important amongst such imperatives will be ones which regulate the order in which the rules of the logical system concerned are to be applied, For at each stage when one is using a logical system, there is a very large number of alternative steps, any of which one is permitted to apply, so far as obedience to the rules of the logical system is concerned. These choices make the difference between a brilliant and a footling reasoner, not the difference between a sound and a fallacious one. Propositions leading to imperatives of this kind might be "When Socrates is mentioned, use the syllogism in Barbara" or "If one method has been proved to be quicker than another, do not use the slower method." Some of these may be "given by authority," but others may be produced by the machine itself, e.g. by scientific induction. The idea of a learning machine may appear paradoxical to some readers. How can the rules of operation of the machine change? They should describe completely how the machine will react whatever its history might be, whatever changes it might undergo. The rules are thus quite time-invariant. This is quite true. The explanation of the paradox is that the rules which get changed in the learning process are of a rather less pretentious kind, claiming only an ephemeral validity. The reader may draw a parallel with the Constitution of the United States. An important feature of a learning machine is that its teacher will often be very largely ignorant of quite what is going on inside, although he may still be able to some extent to predict his pupil's behavior. This should apply most strongly to the later education of a machine arising from a child machine of well-tried design (or programme). This is in clear contrast with normal procedure when using a machine to do computations one's object is then to have a clear mental picture of the state of the machine at each moment in the computation. This object can only be achieved with a struggle. The view that "the machine can only do what we know how to order it to do,"' appears strange in face of this. Most of the programmes which we can put into the machine will result in its doing something that we cannot make sense (if at all, or which we regard as completely random behaviour. Intelligent behaviour presumably consists in a departure from the completely disciplined behaviour involved in computation, but a rather slight one, which does not give rise to random behaviour, or to pointless repetitive loops. Another important result of preparing our machine for its part in the imitation game by a process of teaching and learning is that "human fallibility" is likely to be omitted in a rather natural way, i.e., without special "coaching." (The reader should reconcile this with the point of view on pages 23 and 24.) Processes that are learnt do not produce a hundred per cent certainty of result; if they did they could not be unlearnt. It is probably wise to include a random element in a learning machine. A random element is rather useful when we are searching for a solution of some problem. Suppose for instance we wanted to find a number between 50 and 200 which was equal to the square of the sum of its digits, we might start at 51 then try 52 and go on until we got a number that worked. Alternatively we might choose numbers at random until we got a good one. This method has the advantage that it is unnecessary to keep track of the values that have been tried, but the disadvantage that one may try the same one twice, but this is not very important if there are several solutions. The systematic method has the disadvantage that there may be an enormous block without any solutions in the region which has to be investigated first, Now the learning process may be regarded as a search for a form of behaviour which will satisfy the teacher (or some other criterion). Since there is probably a very large number of satisfactory solutions the random method seems to be better than the systematic. It should be noticed that it is used in the analogous process of evolution. But there the systematic method is not possible. How could one keep track of the different genetical combinations that had been tried, so as to avoid trying them again? We may hope that machines will eventually compete with men in all purely intellectual fields. But which are the best ones to start with? Even this is a difficult decision. Many people think that a very abstract activity, like the playing of chess, would be best. It can also be maintained that 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. This process could follow the normal teaching of a child. Things would be pointed out and named, etc. Again I do not know what the right answer is, but I think both approaches should be tried. We can only see a short distance ahead, but we can see plenty there that needs to be done. -------------------- It's an extraordinarily wonderful collection of charts that demonstrate the history and the current status of the discussion on whether computers (particularly the digital algorithmic machines we have been using today, which is I guess the only computing structure human beings can so far build in a sophisticated manner). I‘ll just read it through as I translate it and hope I myself will also get some idea about this topic along the way. The discussion is divided into 7 parts (maps) comprehensively talking about this issue in different sub-topics or from different perspectives, with a huge diagram that depicts the relationships between arguments (normally either supporting or disputing) presented in each of these maps. Be aware that the disciplines covered by the discussion of such a subject as this (which I guess might be one of very few fundamental problems universe-wide) can naturally include but not be limited to, in a variety of depths and complexity, computing theory, system science, mathematics, physics (very advanced), biology, and philosophy (of different types concerning very fundamental issues). So it's absolutely all right to stop anywhere you feel uncomfortable. This thing was first seen by me in the posters on the 2nd floor of ISE building of University of Canberra, and instantly raised my curiosity as it's a question I have long been thinking about. One great thing of it is it also exhibited how to make appropriate quotation and how important it is, which is mandated and valued by western academics and matched what I was struggling to get used to in the first semester. Comments by the translator might be made and attached to related arguments, but they are only in English. == End of foreword == Issue Area: Can computers have free will 问题领域: 计算机能否具有自由意志 Link to the corresponding part of the map: http://www.macrovu.com/CCTWeb/CCT1/CCTMap1FreeWill.html 1. Alan Turing 1950 (widely recognized as the father of modern computers; Each map in this collection starts with his opinion to pay tribute to him -- translator) 阿兰·图灵 1950 Yes, Machines can (or will be able to) think. A computational system can possess all important elements of human thinking or understanding. 'I believe that at the end of the century ... one will be able to speak of machines thinking without expecting to be contradicted. (from Turing's point of view, i guess, 'without being contradicted' means being able to meet his criteria for determining if a machine can think/behave as a human does -- translator) 是的,机器能够(或将能够)思考。一个计算系统能够具有所有的人类思考或理解(过程或所需)的重要属性。 “我相信,在这个世纪末(二十世纪——编者) ... 人们能够谈论机器思考,而不会有任何矛盾” 2. (disputing 1) Computers can't have free will. Machines only does what they have been designed and programmed to do. They lack free will, but free will is necessary for thought. Therefore, computers can't think. Free will: The ability to make voluntary, unconstrained decisions. Freely made decisions are independent of the influence of such deterministic factors as genetics (nature) and conditioning (nurture) (驳斥1) 计算机不能具有自由意志。机器只能做它们被设计或编程要做的事。他们缺乏自由意志,但自由意志是思考的必要条件。因此,计算机不能思考。 自由意志: 做出自愿、不受约束的决定的能力。自由作出的决定是不依赖于决定性因素如遗传基因(自然)和后天调节(培养)的。 3. (disputing 2) Humans also lack free will. Whether or not computers have will is irrelevant to the issue of whether computers can think. People can think, and they don't have free will. People are just as deterministic as machines are. So machine may yet be able to think. (驳斥2) 人类也没有自由意志。计算机是否具有自由意志与计算机能否思考这个问题无关。人能够思考,但他们不具有自由意志。人和机器一样(至少类似——编者)都是受决定性因素支配的。因此机器仍有可能会思考。 4. (supporting 3) Ninian Smart, 1964, Humans are programmed. If you accept determinism, then you accept that nature has programmed you in certain way and in certain contexts, even though that programming is subtler than the programming a computer receives. (支持3) Ninnian Smart, 1964, 人类也是被编程的。如果你接受决定论,那么你就会接受自然也对你以某种方式在某个特定环境下实施了“编程”,即使这种编程要比计算机编程要复杂(得多——编者) 5. (supporting 3) Free will is an illusion of experience. We may think we are free, but that is just an illusion of experience. Actually, we are determined to do what we do by our underlying neural machinery. According to the modern scientific view, there is simply no room at all for "freedom of the human will" (1986, p. 306)Marvin Minsky Human beings are slaves of brute matter, compelled to act in particular ways by virtual of biochemical and neuronal factors. What we see is the illusory nature of free will (1985, p. 109) Geoff Simons (支持3) 自由意志是经验的幻觉。我们可能觉得我们是自由的,然而这只是经验的幻觉。事实上,我们底部的神经机制决定了我们会做什么。 根据现代科学观点,“人类的意志自由”几乎没有可能。(1986,306页) Markin Minsky 人类是(生物性?——编者)蛮力的奴隶,被迫使以特定方式借助生物化学和神经机能因素行动。我们所见到的是自由意志的虚幻特性。(1985,109页) Geoff Simons 6. (disputing 2) Philip Johnson-Laird, 1988a, Free will results from a multilevel representational structure. A multilevel representational structure is capable of producing free will. The system must have levels for: - representing options for action (e.g. go to dinner, reader, take a walk); - representing the grounds for deciding which option to take (e.g., choose the one that makes me happy, choose by flipping a coin); - representing a method for deciding which decision-making process to follow (e.g. follow the most 'rational' method, follow the fastest method). Computers that have been programmed with such multilevel structures can exhibit free will. (反驳2) Philip Johnson-Laird,1988a,自由意志是一个多层表示结构。一个多层表示结构有能力产生自由意志。这个系统必须含有以下层: - 表示行动选项 (例如:去吃饭,看书,散步); - 表示决定选择哪个选项的考量 (例如:选择使我高兴的选项,或掷个硬币); - 表示选择哪个决策过程的方法 (例如:选择最理性的方式,或选择最快决策方法) 7. (Disputing 2) Geoff Simon, 1985, Free will is a decision-making process.Free will is a decision-making process characterized by selection of options, discrimination between clusters of data, and choice between alternatives. Because computers already make such choices, they possess free will. (Too naive? -- translator) (反驳2) Geoff Simon, 1985, 自由意志是一个决策过程。自由意志是一个由选项选择,数据区分以及多可选项选择所表征的决策过程。由于计算机已经能做这些选择,它们具有自由意志。 8. (Supporting 7) Geoff Simons, 1985, Conditional jumps constitute free will.The ability of a system to perform conditional jumps when confronted with changing information gives it the potential to make free decisions. For example, a computer may or may not "jump" when it interprets the instruction "proceed to address 9739 if the contents of register A are less than 10." The decision making that results from this ability frees the machine from being a mere puppet of the programmer. (支持7) Geoff Simons,1985,条件跳转构成自由意志。系统在遇到变化的信息执行条件跳转的能力使他具有自由决策的潜能。例如,一个计算机可能在解释指令“如果寄存器A的内容小于10的时候则”的时候去跳转(或不跳转)。由这样的能力所导致的决策将使机器从程序员的玩偶中解放出来。 9. (Disputing 2) Alan Turing, 1951, Machines can exhibit free will by way of random election.Free will can be produced in a machine that generates random values, for example, by sampling random noise. (That's what i used to think and still half believe -- translator) (反驳2) 阿兰·图灵,1951,机器能够通过随机选择实现自由意志。自由意志能通过一个能产生随机数的机器制造出来,例如,通过采样随机噪声。 10. (Supporting 9) Jack Copeland, 1993, Free will arises from random selection of alternatives in nil preference situations.When an otherwise deterministic system makes a random choice in a nil preference situation, that system exhibits free will. A nil preference situation is one in which an agent must choose between a variety of equally preferred alternatives (for example, whether to eat one orange or another from a bag of equally good oranges). The available alternatives may have arisen from deterministic factors, but "when the dice roll", the choice is made freely. (支持9) Jack Copeland,1993,自由意志从均偏好情形的随机选择中产生。当一个通常决定性的系统对一个均偏好情形作出随机选择的时候,这个系统就展示出了自由意志。在均偏好情形中一个工作者必须从一组优势等同的选项中做出选择(例如一堆完全相同的橘子)。这些可选选项可能从决定性过程中产生,但“一旦掷了骰子”,这个决定就自由作出了。 11. (Disputing 9) Randomization sacrifices responsibility. Machines that make decisions based on random choices have no responsibility for their actions, because it is then a matter of chance that they act one way rather than another. Becasue responsibility is necessary for free will, such machines lack free will. (反驳9) 随机数牺牲了责任意识。凭借随机数做决策的机器不为它们的行为负责,因为如此他们根据机会作出选择。因为责任是自由意志的必要组成部分,这样的机器不具备自由意志。 12. (Supporting 11) A.J.Ayer, 1954, Free will is necessary for moral responsibility.Randomness and moral responsibility are incompatible. We cannot be responsible for what happens randomly any more than we can be responsbile for what is predetermined. Becasue any adequate account of moral responsibility should be grounded in the notion of free will, randomness cannot adequately characterize free will. (支持11) A. J. Ayer,1954,自由意志是道德责任所必需。随机选择和道德责任是不相容的。我们不能对随机发生的事情比对决定的事情作出更负责的行为。因为任何恰当的道德责任的阐述必须基于自由意志概念,随机选择不能恰当地表征自由意志。 13. (Disputing 11) Jack Copeland, 1993, Random choice and responsibility are compatible.An agent that chooses randomly in a nil preference situation (one in which all choices are equally preferred) is still responsible for its actions. A gunman can randomly choose to kill 1 of 5 hostages. He chooses at random, but he is still responsible for killing the person whom he picks, because he was responsible for taking the people hostage in the first place. Random choice only revokes responsibility if the choice is between alternatives of differing ethical value. (反驳11) Jack Copeland,1993,随机选择和责任是兼容的。一个在均偏好情形中随机选择工作体(所有选择具有相同的偏好)仍旧对其行为要负责。一个杀手能从5个人质中随机选择一个射杀。他随机选择,但他仍旧要对他射杀他选的这个人负责,因为他首先需要对他将这些人扣为人质(并潜在地杀死)这个行为负责。随机选择只有在选择在具有不同的道德价值的选项之间作出的时候才回避了责任。 14. (Disputing 9) The helpless argument. When agents (human or machine) make choices at random, they lack free will, because their choices are then beyond their control. As J. A. Shaffer (1968) puts it, the agent is "at the helpless mercy of these eruptions within him which control his behavior." (反驳9) “无助观点”。当工作体(人或机器)随机选择时,他们不具有自由意志,因为他们的选择不为他们控制。如J. A. Shaffer(1968)指出,工作体无助地处在它体内控制其行为的随机爆发的掌控之下。 15. (Disputing 14) Jack Copeland, 1993, The Turing randomizer is only a tiebreaker.The helplessness argument is misleading, because it implies that random processes control all decision making -- for example, the decision of whether to wait at the curb or jump out in front of an oncoming truck. All the Turing randomizer does is determine what a machine will do in those situations in which options are equally preferred. (反驳14) Jack Copeland,1993,图灵随机发生器只是一个平局突破器。“无助观点”是有误导性的,因为它错误假设了随机过程控制了所有的决策——例如,决定在卡车开过来的时候是呆在人行道上还是跳下去这样的问题。图灵随机发生器其实只是用在所有选项都是相同偏好的情形。 16. (Disputing 2) Jack Copeland, 1993, Being a deterministic machine is compatible with having free will.Humans and computers are both deterministic systems, but this is compatible with their being free. Actions caused by an agent's beliefs, desires, inclinations, and so forth are free, because if those factors had been different, the agent might have acted differently. (反驳2) Jack Copeland,1993,成为决定性机器是和拥有自由意志兼容的。人类和计算机都是决定性系统,但是这是与他们的自由相兼容的。由一个工作体的信仰,欲望,(性格、偏好——编者)倾向及其它产生的行为是自由的,因为假设这些因素不同,那么工作体的行为也不同。 17. (Supporting 2) Computers only exhibit the free will of their programmers.Computers can't have free will because they cannot act except as they are determined to by their designers and programmers. (支持2) 计算机只能呈现为它们编程的人的自由意志。计算机不能获得自由意志因为它们不能以不同于他们被设计和编程的方式运作。 18. (Disputing 17) Geoff Simons, 1985, Some computers can program themselves. Automatic programming system (APs) write computer programs by following some of the same heuristics that human programmers use. They specify the task that the program is to perform, choose a language to write the program in, articulate the problem area the program will be applied to, and make use of information about various programming strategies. Programs written by such APs are not written by humans, and so computers that run those programs do not just mirror the free will of humans. (反驳17) Goeff Simons,1985,有些计算机能自己编程。自编程系统(APs)通过遵循一些人类程序员用的启发式方法写计算机程序。它们能够指定程序要执行的任务,选择一个语言来写这个程序,描述这个程序适用的问题域,并利用关于不同编程策略的信息。有这种系统编写的程序不是人写程序,因此写这些程序的计算机并不简单地反映人类的意志。 19. (Supporting 17) Paul Ziff, 1959, Preprogrammed robots can't have psychological states.Because they are programmed, robots have no psychological states of their own. They may act as if they have psychological states, but only because their programmers have psychological states and have programmed the robots to act accordingly. (支持17) Paul Ziff,1959,预编程的机器人没有心理活动和状态。因为他们是被编程的,计算机不具有它们自己的心理状态。它们可能会像具有心理状态那样行动,但这只是因为程序员具有心理活动并将其相应地编程到机器人中。 20. (Disputing 19) Ninian Smart, 1964, Preprogrammed humans have psychological states.If determinism is true, then humans are programmed by nature and yet have psychological states. Thus, if determinism is true, we have a counterexample to the claim that preprogrammed entities can't have psychological states.Supported by "Humans are Programmed." Box 4. de-ter-min-ism: The belief that all actions and events are determined by the influences of nature and history. Human actions result from strict causal laws that describe the brain and its relation to the world. Free will is an illusion. (反驳19) Ninian Smart,1964,预编程的人具有心理状态。如果决定论是正确的,那么人类是由自然编程的,却也具有心理状态。因此,如果决定论是正确的,我们就有了一个反例,以驳斥预编程的实体不能具有心理状态。被“人类是被编程的”,第4框支持。 决定论:所有行动和实践是由自然和历史的影响所决定的一种观点。人类行为是由严格的描述大脑及其与世界关系的定律所规定的。自由意志是一个幻象。 21. (Supporting 19) The record player argument. A robot 'plays' its behavior in the same way that a phonograph plays a record. It is just programmed to behave in certain ways. For example, "When we laugh at the joke of a robot, we are really appreciating the wit of a human programmer, and not the wit of the robot" (Putnam, 1964, p. 679). (This argument is not so appealing to me who at least knows some advanced stuff that a modern computer can do -- translator) (支持19) 录音机观点。一个机器人“播放”它的行为就像一台留声机播放碟片。他只是被编程而做出某些行为。例如,“当我们对一个机器人的笑话大笑的时候,我们实际上是在欣赏这个程序员的把戏而不是这个机器人的” (Putnam,1964,679页)。 22. (Disputing 21) Hilary Putnam, 1964, The robot learning response. A robot could be programmed to produce new behavior by learning in the same way humans do. For example, a program that learned to tell new jokes would not simply be repeating jokes the programmer had entered into its memory, but would be inventing jokes in the same way humans do (but how? more details needed -- translator) (反驳21) Hilary Putnam,1964,机器人的学习反馈。机器人能够被编程为像人类一样通过学习产生新的行为。例如,一个能够学着说新笑话的程序将不会简单重复程序员预先设定的笑话,而会像人类一样发明新的笑话。 23. (Supporting 19) Paul Ziff, 1959, The reprogramming argument. Humans can't be reprogrammed in the arbitrary way that robots can be. For instance, a robot can be programmed to act tired no matter what its physical state is, whereas a human normally becomes tired only after some kind of exertion. The actions of the robot depend entirely on the whims of the programmer, whereas human behavior is self-determined. (To me, this, the physical link, is a very insightful and promising argument -- translator) (支持19) Paul Ziff,1959,重编程观点。人类不能被像对机器人那样以任意方式重编程。例如,一个机器人能够被编程为无论在任何身心(物理)状况下都觉得累的样子,但人类通常只会在劳作之后才感到疲惫。机器人的行为完全依赖于程序员的奇想,而人类的行为则是自决定的。 24. (Disputing 23) Hilary Putnam, 1964, Reprogramming is consistent with free will.The reprogramming argument fails to show that robots lack free will for the following reasons. - Human can be reprogrammed without affecting their free will. For example, a criminal might be reprogrammed into a good citizen via a brain operation, but he could still make free decisions (perhaps, for example, deciding to become a criminal once again). - Robots cannot always be arbitrarily reprogrammed in the way that the programming argument suggests. For instance, if a robot is psychologically isomorphic to a human, it cannot be arbitrarily reprogrammed. (Interesting, structurally the same. This one is very strong, but it assumes such a robot exists -- translator) - Even if robots can be arbitrarily reprogrammed, this does not exclude them from having free will. Such a robot may still produce spontaneous and unpredictable behavior. (My suggestion is that we need to be very cautious of the use of the word 'unpredictable' esp in what context and for what purpose it is used as this entire discussion is concerned -- translator) "Look, that robot's been reprogrammed but it still acts spontaneously and unpredictably" (反驳23) Hilary Putnam,1954,重编程和自由意志不矛盾。重编程观点没能恰当地证明机器人无法获得自由意志,基于以下理由: - 人类能在不影响他们自由意志的情形下被“重编程”。例如,一个罪犯可能通过脑手术被重编程成为一个好公民,但是他仍能作自由决定(或许,例如,决定是否重新变成一个罪犯) - 机器人不能总是依照可编程参数所提示的那样被随意编码。例如,如果一个机器人被“心理学地”制作成和人类同构(本人很喜欢这个概念,代数里的这个概念和这里的意义或许极相近——编者),它就不能被随意重编程。 - 即使机器人能被重编程,这也不能使其排除在自由意志之外。如此的机器人将仍能产生自发和不可预测的行为。 “看哪,那个机器人已经被重编程,但它仍旧自说自话” 25. (Supporting 2) L. Jonathan Cohen, 1955, Computers do not choose their own rules.We refer to people as "having no mind of their own" when they only follow the rules or commands of others. Computers are in a similar situation. They are programmed with rules and follow commands without conscious choice. Therefore, computers lack free will. (so powerful that no dispute is given in the map, one more word from the translator, it can be roughly seen that the rule the computer has has to be the same as that the program has, or the (run-time) rule is either, ill-implemented (i.e. a bug), altered erroneously when running, or making no sense -- translator) (支持2) L. Jonathan Cohen, 1955, 计算机不能选择他们自己的准则。我们将人们说成“没有脑子”当他们盲从别人指定的规则和命令。计算机也遇到类似处境。它们根据规则和命令(一种总体原则——编者)被编程,而没有自觉的选择。因此,计算机不具有自由意志。 26. (Supporting 2) Joseph Rychlak, 1991, Computers can't do otherwise.An agent's actions are free if the agent can do otherwise than perform them. This means that an agent is free only if it can change its goals. But only dialectical reasoning allows an agent to change its goals and thereby act freely. Because machines are not capable of that kind of thinking, they are not free. (again a nice point, but lacking of clarity) Note: Also, see the 'Can physical symbol systems think dialectically?' arguments on Map 3. (支持2) Joseph Rychlak,1991,计算机不能以其他方式行事(只能以单一方式做事情——编者)。一个工作体的行动是自由的,只有在该行动体能选择做执行这些行动之外的事。这意味着,一个工作体是自由的,只在其能够改变他的目标。然而,只有辩证逻辑才能允许一个工作体更改其目标并因此自由行动。因为计算机不能做这样的思考,他们不是自由的。 27. (Supporting 2) Selmer Bringsjord, 1992, Free will yields an infinitude that finite machines can't reproduce. Unlike deterministic machines (e.g., Turing machines), persons can be in an infinite number of states in a finite period of time. That infinite capacity allows persons to make decisions that machines could never make. (again too powerful and too close to the fundamental level to be challenged; still more detailed proof needs to be given but it's not so hard as some of the above) Note: Bringsjord's argument is fleshed out in the 'Can automata think?' arguments on Map 7. Also, see 'Can computers be persons?' arguments on this map. (支持2) Selmer Bringsjord,1992,自由意志产生无限性而有限(自动)机不能产生之。不像决定性机器(例如图灵机),人能够在一个给定有限时间内处于无限状态。这种无限容量使得人类能做出机器不能仿照作出的选择和行为。 注:Bringsford的论调在第七图“自动机能否思考”中更详细讨论。也见在本张图上“计算机能否成为人?”区的讨论。