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Computing Machinery and Intelligence Essay

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Computing Machinery and Intelligence Essay

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Write an essay of about 750 words, according to the article I provided. You can use some references from website and in-test citations but not too much, for example “It is not possible to produce a set of rules purporting to describe what a man should do in every conceivable set of circumstances. ” (A. M. Turing, 1950).

please don’t copy from anywhere.

You can create a positive topic by your own words base on question “: Do you think that the Turing test is a useful gauge for machine intelligence? Why or why not?”

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A. M. Turing (1950) Computing Machinery and Intelligence. Mind 49: 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 discretestate 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.

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