University of Toronto, Department of Computer Science
CSC 2501F—Computational Linguistics, Fall 2018
Reading assignment 1
Due date: In class at 11:10, Thursday 13 September 2018.
Late write-ups will not be accepted without documentation of a medical or other emergency.
This assignment is worth 5% of your final grade.
What to read
Alan Turing, “Computing machinery and intelligence”, Mind, 59, 1950, 433–460.
Reading guide: Read sections 1–2; skip sections 3–5. In section 6, look at subsections (1)–
(3) and (7)–(9), but don’t use them in your argument; consider subsections (4)–(6) carefully.
Look at section 7, and give it some thought, especially from the second paragraph on page
458 (starting “The idea of a learning machine”) through to the end.
What to write
Consider the question “Could a machine ever use and understand language the way people
do?”, and write a brief summary of the arguments on both sides of the question, from the
perspective of 2018. How could we resolve the question?
Some points to consider:
• Turing was asking a related but different question: “Could a machine think?”.
• A lot has been learned since 1950 about what machines can and can’t do. The research
fields of artificial intelligence and machine learning have had many successes and
failures.
General requirements: Your write-up should be typed, using 12-point font and 1.5-line
spacing; it should fit on one to two sides of a sheet of paper. Hand in one copy at the begin-
ning of class.
Computing Machinery and Intelligence
A. M. Turing
Mind, New Series, Vol. 59, No. 236. (Oct., 1950), pp. 433-460.
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[October, 1950
M I N D
A Q U A R T E R L Y R E V I E W
PSYCHOLOGY AND PHILOSOPHY
I.-COMPUTING MACHINERY AND
INTELLIGENCE
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 i t is difficult to escaDe the conclusion that the meaning a
and the answer to tlie auestion, ‘ Can machines think ? ‘ is to be
sought in a statistical sirvey sdch 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 ‘. I t 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
from 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
thas :
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
28 433
434 A. M. TURING :
object in the game to try and cause C to make the wrong identi-
fication. 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 arrangeljaent 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 adoj 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. I t is possible
that a t some time this might be done, but even supposing this in-
vention 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 Porth
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.
COMPUTING MACHINERY AND INTELLIGENCE 435
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 conditioiis
of our game make these disabilities irrelevant. The ‘witnesses ‘
can brag, if they consider i t 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 a t once by slowness
and inaccuracy in arithmetic. May not machines carry out some-
thing 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 i t will be assumed that the best strategy 1s
to try to provide answers that would naturally be given by a man.
3. The Machines concerned i n the Game.
The question which we put in 9 1 will not be quite definite
until we have specified what we mean by the word ‘ machine ‘.
I t 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 t$e team of
436 A. M. TURING :
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 i t 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 com-
puters which would do well. But this is only the short answer.
We shall see this question in a different light later.
4. Digital Compute~s.
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
COMPUTING MACHINERY AND INTELLIGENCE 437
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 head 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
pads 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 opera-
tion 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 in-
struction such as
438 A. M. TURING :
‘Now obey the instruction stored in position 5606, and con-
tinue 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 repeated 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 tolls 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 com~uter
I
as using is of course a convenient fiction. Actual human com-
puters 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 instn~ction table.
Constructing instruction tables is usually described as ‘ pro-
gramming ‘. To ‘ programme a machine to carry out the opera-
tion 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). I t is not normally possible i;o 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 T.
Most actual digital computers have only a finite store. There
is no theoretical difficulty in the idea of a computer with an un-
limited store. Of course only a finite part can have been used
at any one time. Likewise only a finite amount can have been
COMPUTING MACHINERY AND INTELLIGENCE 439
oonstructed, 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,
Luca,sian 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 verv
attractive prospect. h he speed which would have been availabie
would be definitely faster than a human computer but ~omet~hing
like 100 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. Import-
ance 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 com-
puters are in a sense equivalent, we see that this use of olectri~it~y
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 i t 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 look 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 sufficientlv 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
440 A. N. TURISG
round through 120″ once a second, but may be stopped by a
lever which can be operated from outside ; in addition a lamp is
to light in one of the positions of tlie wheel. This machine could
be described abstractly as follom~s. The internal state of the
machine ( ~ ~ h i c h is described by the position of the wheel) may be
q,, q, or q,. There is an input signal i, or il (position of lever).
The internal state at any moment is determined by the last state
and input signal according to the table
Last State
Pi Pa 43
The output signals, the only externally visible indication of
the internal state (the light) are described by the table
state q1 q2 q3
Output 0, 0, 0,
This example is typical of discrete state machines. They can be
described by such tables provided they hare 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 a t a later time. The displacement of a
single electron by a billionth of a centimetre a t 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 a t one
moment yields reasonably accurate knowledge any number of
steps later.
COMPUTING MACHINERY AND ISTELLIGENCE 441
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
i t about 216690001 Compare this with our example i.e. about 10509000.
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 10100X50X30, i.e. 101509000.
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 exam~le about 1.6. If
two’ machines are put together their capaciti& must be added
to obtain the capacity of the resultant machine. This leads to
the ~ossibilitv of statements such as ‘ The Manchester machine
contiins 64 *agnetic 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 corres~ondin~ to a discrete state machine it
is possible to predict whit it $11 do. There is no reason why
this calculation should not be carried out by means of a digital
computer. Provided i t could be carried. out sufficiently quickly
the digital computer could mimic the behaviour of any discrete
state machine. The imitation game could then be played with the
machine in questian (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 urziversal machines. The existence of machines
with this property has the important consequence that, consi-
derations of speed apart, i t is unnecessary to design various new
maohines to do various computing processes. They can all, be
442 A. M. TURING :
done with one digital computer, suitably programmed for each
case. It will be seen that as a consequence of this all digital com-
puters are in a sense equivalent.
We may now consider again the point raised at the end of 53.
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. Cont~ary Views on the Main Question:
We may now consider the ground to have been cleared aud we
are ready to proceed to the debate on our question, ‘Can machines
think ? ‘ and the variant of it quoted a t the end of the last section.
We cannot altogether abandon the original form 3f the problem,
for opinions will differ as to the appropriateness of the substitu-
tion 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 i t will be possible
to programme computers, with a storage capacity of about lo9,
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 worde 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 unproved conjecture, is quite mistaken. Provided i t 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.
443 COMPUTING MACHINERY AND INTELLIGENCE
I now proceed to consider opinions opposed ts my own.
(1) T h e 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 omni-
potence 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 soul. An argument of exactly similar
form may be made for the case of machines. I t 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 con-
sider the circumstances suitable for conferring a soul. The cir-
V
cumstances 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 c roc re at ion of children: rather we me. in either
case, instrumenis 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,
Possibly this view is heretical. St; Thomas Aquinas (Summa Theologica,
quoted by Bertrand Russell, p. 480) states that God cannot make a man
to have no soul. But this may not be a real restriction on His powers, but
only a result of the fact that men’s souls are immortal, and therefore
indestructible.
444 A. M. TURING :
that it should not move a t any time ” (Psalm cv. 5) were an
adequat’e refutation of the Copernican theory. With our present
knowledge such an argument appears futile. When that know-
ledge was not available i t made a quite different impression.
(2) The ‘Heads in the Sand ‘ Objection. “The consequences
of machines t,hinking 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 h s commanding
,position. The popularity of the theological argument is clearly
connected with this feeling. I t is likely to be quite strong in in-
tellectual 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,l 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,
Kleene, Rosser, and Turing. The latter .result is the most con-
venient to consider, since i t 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 far a reply.
There may, of course, be many such questions, and questions
which cannot be answered by one machine may be satisfactorily
Author’s names in italics refer to the Bibliography.
answered by another. We are of course supposing for the present
that the auestions 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 quest’ion ? ” The dots are to be replaced by a des-
cription of some machine in a standard form, which could be
somet’hing 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 of any
particular machine, it has only been stated, without any so&
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 onlv 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 aga,in there might be other machines cleverer
again, and so on.
Those who hold to the mathematical argument would, I think,
mostly be willing to accept the imitation game as a basis for
discussion. Those who believe in the two previous obiections
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 auote. ” 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 Iaow that
it had written it. No mechanism could feel (and not merely
446 A. M. TURING :
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 de-
pressed 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 a machine thinks is to be
the machine and to feel oneself thinking. One could then des-
cribe 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. I t 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 con-
vention 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 : I t 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.
1nterroga.tor: 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 ?
do not know whether he would regard the machine as ‘ merely
I
COMPUTING MACHINERY AND INTELLIGENCE 447
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 (p. 448), have initiative,
have a sense of humour, tell right from wrong, make mistakes
(p. 448), fall in love, enjoy strawberries and cream (p. 448), make
some one fall in love with it, learn from experience (pp. 456 f.),
use words properly, be the subject of its own thought (p. 449),
have as much diversity of behaviour as a man, do something
really new (p. 450). (Some of these disabilities are given special
consideration as indicated by the page numbers.)
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. Prom 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.
448 A. M. TURING :
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, I 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 con-
tributes -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. I t 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 unsuit-
able 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
COMPUTING MACHINERY AND INTELLIGENCE 449
011 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 con-
clusion 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. Tilere is clearly
no reason at all for saving that a machine cannot malie this
kind of mistalie. I t m k h r d o nothing but type out repeatedly
‘ 0 = 1 ‘. 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. Kever-
theless, ‘ 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 – 40% – 11 = 0 one would be tempted to de-
scribe 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. I t may be used to help in making
up its own programmes, or to predict the effect of al~erations in
i.ts own structure. By observing the results of its own behaviour
it can modify its own programmes so as to achieve some purpose
more effectivelv. 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 i t 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 main-
tains that a machine can do one of these things, and describes the
kind of method that the machine could us; one will not make
29
450 A. M. TURING :
much of an impression. It is thought that the method (whatever
it mav be, for it must be mechanical) is reallv rather base.
Compare the parenthesis in Jefferson’s statement quoted on p. 21.
( 6 ) Lady Lovelace’s Objection. Our most detailed information
of Babbage’s Analytical Engine comes from a memoir by Lady
Lovalace. In it she states, “The Analytical Engine has no pre-
tensions to originate anything. It can do whatever we hzow how
to order it to perform ” (her italics). This statement is quoted
by Hartree (p. 70) 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 mould 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 i t 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 thab 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 Babbaee. In anv case there was no
obligation on them to claim all t h l t could be claimed.
This whole question will be considered again under the heading
of learning machines.
A variant of Ladv Lovelace’s obiection 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 bk met directlv. Machines take me bv surmise wiFh
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,
takingUrisks. Perhaps I say to myself, ‘ I suppose the voltage
here ought to be the same as there : anyway let’s assume i t is ‘.
COAIPUTING MACHINERY AND INTELLIGENCE 451
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 pro-
bably say that such 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 i t is perhaps worth remarking that the appreciation of some-
thing 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 resented to a mind all conseauences of that fact
spring into the mind simultaneously with it. It is a very use-
ful assumption under many circumstances, but one too easily
forgets that i t is false. A natural consequence of doing so is that
one then assumes that there is no virtue in the mere work in^
u
out of consequences from data and general principles.
(7) Argument from Cor~tinuityin the Nervous System. The
nervous system is certainly not a discrete-state machine. A
small erro; in the informatidn 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 svstem.
It is true that a discrete-state machine musc be different from
a continuous machine. But if we adhere to the conditions of tlie
imitation game, the imerrogator will not be able to take any
advantage of this difference. The situation can be made clearer
if we consider some other simpler continuous machine. A
differential analyser ill do very well. (A differential analyser
is a certain kind of machine not of the discrete-state tvue used
for some kinds of calculation.) Some of these provfie their
answers in a typed form, and so are suitable for taking part
in the game. It ~\-ould not be possible for a digital computer
to predict exactlv what answers the differential analvser
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 n. (actually about 3.1416) it would be reasonable
452 A. M. TURING :
to choose a t 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 verv 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 th; 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 un-
distributed 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 lam. 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
COMPUTING MACHINERY AND INTELLIGENCE 453
such laws if they existed. Then given a discrete-scate machine
it should certainly be possible to discover by observation sufficent
about it to predict its future behaviour, and this within a reason-
able 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 1000 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 Extra-Sensory Perception. I assume
that the reader is familiar with the idea of extra-sensory per-
ception, and the meaning of the four items of it, viz. telepathy,
clairvoyance, precognition and psycho-kinesis. These disturb-
ing 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 E.S.P. ; 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 E.S.P. may be especially relevant.
A more specific argument based on E.S.P. 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 clair-
voyance 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 com-
puter 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 psycho-kinetic
powers of the interrogator. Perhaps this psycho-kinesis might
cause the machine to guess right more often than would be
expected on a probability calculation, so that the interrogator
454 A. 31. TURING :
might still be unable to make the right identification. On the
other hand, he might be able to guess right without any question-
ing, by clairvoyance. With E.S.P. 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 ‘ telep~thy-proof room ‘ ~vould
satisfy all requirements.
7. Learning J4achines.
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 vie\+-s. 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 sap 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, the disturbance caused by such an incoming
neutron mill 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
‘ sub-critical ‘, i.e. to correspond in this analogy to piles of sub-
critical size. An idea presented to such a mind will on average
give rise to less than one idea in reply. A smallish proportion
are super-critical. An idea presented to such a mind map give
rise to a whole ‘ theory ‘ consisting of secondary, tertiary and
more remote ideas. Animals minds seem to be very definitely
sub-critical. Adhering to this analogy we ask, ‘ Can a machine
be made to be super-critical 2 ‘
The ‘ skin of an onion ‘ analogy is also helpful. In considering
the functions of the mind or the brain TT-e 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.
COMPUTING MACHINERY AND INTELLIGENCE 455
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 5 6, will be that provided by
waiting for the end of the century and then doing the experiment
described. But what can we say 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 t,hat tGese will not be adeqclate 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 lo9was 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 lo9.) A storage capacity of lo7
would be a very practicable possibility even by present tech-
. niques. I t is probably not necessary to increase the speed of
o~erations of the machines at all. Parts of modern machines
which can be regarded as analogues 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 programme a day, so that
about sixty workers, working steadily through the fifty years
might accomplish the job, if nothing went into the waste-paper
basket. Some more ex~editious method seems desirable.
In the process of tryi& to imitate an adult human mind we
are bound to think a good deal about the process which has
brought i t 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.
456 A. M. TURING :
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. Pre-
sumably the child-brain is something like a note-book as one
buys it from the stationers. Rather little mechanism, and lots
of blank sheets. (Rlechanism 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 a.n obvious
connection between this process and evolution, by the identifi-
cations
Structure of the child machine = Hereditary material
Changes ,, ,, = Mutations
Natural selection = Judgment of the experimenter
One may hope, how-ever, 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 be 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. I t 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.
COMPUTIKG AIACHINERY AND INTELLIGENCE 457
We normally associate punishments and rewards with the
teaching process. Some simple child-machines can be con-
structed 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 pre-
suppose 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 num-
ber 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 ‘.I
In the latter case the store would be largely occupied with de-
finitions and propositions. The propositions would have various
kinds of status, e.g. well-established facts, conjectures, mathe-
matically 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 im-
perative 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,
Or rather ‘ programmed in ‘ for our child-machine will be programmed
in a digital computer. But the logical system will not have to be learnt.
458 A. M. TURING :
” 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 i t 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 pro-
duced by the machine itself, e.g. by scientific induction.
The id2a 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 mith 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 behaviour. This should apply most strongly to the
COMPUTING MACHINERY AND INTELLIGENCE 459
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 ‘,I appears
strange in face of this. Most of the programmes which we, can
put inbo the machine will result in its doing something that we
cannot make sense of a t all, or which we regard as completely
random behaviour. Intelligent behaviour presumably consists
in a departure from the completely disciplined behaviour in-
volved 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 pp. 24, 25.) 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 (see p. 438). 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
‘
a t 51 then try 52 and go on until we got a number that worked.
Alternatively we might choose numbers a t random until we got a
a good one. This method has the advantage that it is unnecessary
to keep track of the values that have been tried, but the dis-
advantage 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 in-
vestigated 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 svstematic. I t should be noticed that i t is
used in the analogous process of evolution. But there the
systematic method is not possible. How could one keep track
Compare Lady Lovelace’s statement (p. 450), which does not contain
the word ‘only ‘.
of the different genetical combinatiol~s that had been tried, so
as to avoid trying them again ?
We may hope that lnachines 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,
x+-ould be best. It can also be maintained that it is best to
provide the lnaclline with the best sense organs that money can
buy, and then teach it to understand and speak English. This
process conld 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.
EIBLIOGRAPHY
Samuel Butler, Erevhon, London, 1865. Chapters 23, 24, 25, The Book
of the ,IIachines.
Alonzo Church, ” An Unsolvable Problem of Elementary Number Theory “,
American J . of ,?lath., 58 (1936), 345-363.
K. Godel, ” fiber formal unentbcheidbare Satze der Principla Rlathematica
und x-erwandter Systeme, I “, -Ilotzatshefte fur Math. u?zd Phys.,
119311, 173-189.
D. R. Hartree, Cnlculating Instrztments and ~IIachines, New York, 1949.
S. C. Kleene, ” General Recursive Functions of Xatural Numbers “,
American J . of Math., 57 (1935), 153-173 and 219-244.
G. Jefferson, ” The Mind of Mechanical Man “. Lister Oration for 1949.
British ,Ilerlical Journal, vol. i (1949), 1105-1121.
Countess of Lovelace, ‘ Translator’s notes t c an artlcle on Babbage’s
Analytical Engire ‘, Scient~fic ,Ilemozrs (ed. by R. Taylor), vol. 3
(1842), 691-731.
Bertrand Russell, History of Western Philosophy, London, 1940.
A. 31. Turing, ” On Computable Xumbers, with an Application to the
Entscheidungsproblem “, Proc. London ..lIath. Soc. (2), 42 (1937),
230-265.
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