Before I start on today's lecture, I just want to point out something from the last lecture there was, as I pointed out at the time, a misprint.
I've not corrected it. It should say X prime equals x plus one.
That's in slide one five two one five three and one five four.
It previously said X equals x prime plus one, which was the wrong way round.
This is clearly saying X Prime is the successor of X.
That was correct. My gloss on it was mistaken. Sorry about that.
Seems to be fine, Andy. Today we move on from the 1936 paper to the 1950 paper even more famous.
It's one of the most cited philosophical papers ever published computing, machinery and intelligence.
It was published in the prominent journal mined in 1950.
You'll find that there are quite a lot of allusions back to the 1936 paper,
so watch out for those quite a lot of what Turing says is alluding to results that he had proved then.
I'm just putting on the slides here some useful books on the philosophy of AI on the Chinese room argument,
as well as on Turing, will be dealing with cells Chinese room argument next time.
Some useful collections of papers. This one we've already seen.
There's a collection that I edited with Andy Clock back in 1996 that was from a conference commemorating Turing.
And there are seven papers in there that are relevant to the Turing test and also my introduction.
And there's a book devoted to the Chinese room argument that I mention there.
Stanford Encyclopaedia of Philosophy is often very useful on philosophical things quite generally,
and it's got an article on the Turing test and on the Chinese room, and there are some useful web resources.
Andrew Hodges, who wrote the monumental biography of Alan Turing, has a website devoted to him.
Lots of good stuff there and a very long paper with some useful stuff.
I think of more mixed quality, but not all the points made.
There are ones that I'd agree with, but it's got a lot of scholarly material on the Turing test.
They're well worth looking at. OK.
The 1950 paper is perhaps often taken more seriously than it ought to be, and this is a point worth starting with.
This is a quotation from Robin Gandy I think may be the last thing he ever published.
This was in our collection in 1996. The 1950 paper was intended not so much as a penetrating contribution to philosophy, but as propaganda.
He wrote this paper, unlike his mathematical papers, quickly and with enjoyment,
I can remember him reading aloud to me some of the passages always with a smile, sometimes with a giggle.
Some of the discussions of the paper loaded with more significance than it was intended to bear there.
Robin Gandhi was an intimate friend of Turing's.
He was his Ph.D. student. He was Turing's literary executors of Turing left his papers to Gandhi.
He also, interestingly ended up at Oxford, where one of the things that he did was to start the maths and philosophy degree.
Back in 1969, in 1972, modern languages philosophy, modern languages was started in the next degree.
To be started after that in philosophy was computer science philosophy in 2012.
So a bit of a legacy then.
OK, The Imitation Game is Turing's way of reworking the question.
Can machines think? And this is a bit confusing, a bit odd.
I proposed to consider the question Can machines think if the meaning of the words machine and thing?
Could it be found by examining how they commonly used? The answer is to be sought in a statistical survey, but this is absurd.
Instead, I shall replace the question by another, which is closely related to it, but relatively unambiguous.
Now that's a bit peculiar, isn't it? Philosophers are constantly asking questions about the meaning of things like knowledge free will and so on.
And we don't standardly think, well, we could go and do a statistical survey and find out what people say.
But actually the only alternative is to replace it with a completely different question.
So there's something a little bit odd about Turing's procedure, but let's see where it leads.
His replacement question is in the context of an imitation game, and he introduces this in the context of a question over identity.
We have an interrogator in one room who is sending questions to two individuals in two other rooms.
The questions are being sent in text, so Turing suggests a teletype machine.
Here I've actually got Turing statue, and that's an Enigma machine, but it's close enough to a teletype that I've put it in there.
And here we've got Charles Babbage and Ada Lovelace, who I've taken as my sample man and woman it.
When the game is played, the interrogator doesn't actually know the identity of the people concerned has no idea who they are.
Just knows that there's one man and one woman in separate rooms and is sending questions to them in text and is receiving them back in text.
And the interrogators job is to try to work out which is the man, which is the woman.
But the twist on it is that the man is pretending to be a woman.
So if, as Turing says, he asks, How long is your hair?
The man might reply, My hair is shingled, and the longest strands are about nine inches long.
Meanwhile, the woman may be saying, I'm the woman, don't listen to him, and you can imagine other questions that might be asked.
I mean, in the modern context, one might ask who won the Premiership this year?
And the man will respond, Oh, I don't know anything about football. I'll have to ask my boyfriend.
So you can imagine it could be quite fun.
I mean, it seems to have its origin in the sort of Victorian parlour game now.
What the man is trying to do remember is to pretend successfully to be the woman he succeeds in that if the interrogator can't tell who's who.
So if the interrogator ends up essentially tossing a coin, or suppose you play this game repeatedly with different interrogation?
It is, and the man scores about 50 per cent, so the interrogator is only able to get him half the time.
That's pretty much as good as it gets.
It would be a bit peculiar if the man was able to impersonate a woman better than a woman can represent herself.
But. So the interrogators in a different room, tones of voice are ruled out because the answers are purely by text, as you see.
Turing is suggesting a tele printer. And then we get the computer being introduced.
We now ask what will happen when a machine takes the place of a.
That is the deceitful man 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?
That's again, rather peculiar. They replaced the original question.
What does that mean, then the machine? The question was can machines think that looks like it's got a yes or no answer?
Or maybe the answer would be possibly yes. Machines could in principle think, are we really supposed to replace that with the question,
can a machine play The Imitation Game as well as a man can against a woman?
That seems a bit peculiar. Moreover, it's not clear exactly what the computer's job is.
Here is the job to pretend to be a woman, or is the job to pretend to be a human?
That actually does become clear later in Sections two and five of the paper.
It becomes obvious that Turing is seeing the computer as trying to imitate a person.
I mean, he often says a man, but that in 1950, when you say man, you often mean person.
That's changed considerably. So this is the way the Turing test is normally understood.
We've still got the interrogator. We've got the teletype communicating to two different rooms, if you like.
One of them contains a computer running a programme. The other one contains a person could be either man or woman doesn't matter.
And the computer is trying to impersonate a person.
Either man or woman doesn't matter. And the result that Turing seems to be hinting at, he doesn't state it very explicitly.
But this seems to be the drift of his paper that if the interrogator can't reliably distinguish the computer from the human,
then the computer programme must be judged to be intelligent for thinking that that seems to be where he's going.
In Section two of the paper, Turing's idea about what he's doing is clarified.
The interrogators questions can be used to elicit the computer's knowledge about almost any of the fields of human endeavour.
And he gives some examples we'll see in a moment and notice that the set up has the advantage as he points
out of drawing a fairly sharp line between the physical and the intellectual capacities of a person.
So one great advantage of the test is, as we've seen before, the tone of voice isn't taken into account, nor is the physical appearance.
The interrogator doesn't actually see who is responding. All all he gets is the textual responses and has to judge on that basis.
But as Turing says, those textual responses could cover a wide range of things.
So here's an illustrative conversation that he gives.
Please might write me a summit on the subject of the fourth bridge that comes the answer.
Count me out on this one. I never could write poetry. It seems, may seem a rather strange thing to ask.
As your first question, please write me a sonnet, not the sort of thing you would expect to happen in an interactive conversation.
We'll see why Turing gives the example of a sonnet later.
He's responding to Geoffrey Jefferson at thirty four thousand nine hundred fifty seven to
seventy thousand seven hundred sixty four poles about 30 seconds and then give his answer,
other than 5000 621.
Notice Turing is here deliberately having the system pretend to take longer than it needs, so there's a clear element of deception playing a role.
Do you play chess? Yes. And he gives a very simple chess set up, and after a pause of 15 seconds to educate Mate,
I conclude that Turing was not particularly expert at chess if he thought it took 15 seconds to work that one out.
There we go. Yeah, OK.
An obvious objection to the Turing test. It seems to be biased in favour of human thought, and Turing says may not.
Machines carry out something which ought to be described as thinking, but is very different from what a human person does.
And indeed, this seems to be an obvious objection.
I mean, suppose an alien comes down from the planet Zog and takes place that takes part in this test and.
The alien is asked this question and comes back with an answer immediately.
We just know it isn't a human. Certainly not in any sort of normal human.
Does that mean it's not intelligent? No.
On the contrary, if the alien is able to do arithmetic much more quickly than we can, if anything, that suggests it's more intelligent, not less.
And likewise, if you if you ask it, you know, how long is your hair?
What hair? Maybe the aliens on Zog don't have any hair that wouldn't count against its being intelligent.
So it seems odd to have a test which depends on mimicking humans.
Turing's response is that the objection is indeed 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. Now again, he doesn't say very explicitly where he's driving here,
but I take it that this is a strong suggestion that he wants us to take the the test as a sufficient proof of intelligence, but not a necessary test.
So if something passes the Turing test, then we are to deem it intelligent.
The fact that it doesn't pass the test, e.g. because it responds more quickly than a human would should not mean that we counted as unintelligent.
Now I want to just now refer to something later in the paper.
I mean, I'm generally going in this lecture I'm going through,
as you see in sequence through the paper to guide your reading of it, and I please do read it before the next lecture.
I hope you know this will help you to identify the principal points in it.
But later on in Section six, Turing is going to give an example, which I think probably is the best argument for the Turing test.
And it concerns the choice of words in a poem. And here is the dialogue.
So again, we've got this sonnet.
We imagine the interrogator questioning what Turing calls a witness that is one of the people in one of the rooms in the first line of your sonnet,
which reads, Shall I compare this to a summer's day? Wouldn't a spring day do as well?
Or better back comes the answer. It wouldn't scan.
In other words, it would have the wrong rhythm. Shall I compare this to a spring day?
Not enough syllables. How about a winter's day that would scan?
All right. Shall I compare it to a winter's day? Yes, but nobody wants to be compared to a winter's day.
Would you say Mr. Pickwick reminded you of Christmas, then we had an allusion to Shakespeare and a Shakespearean sonnet?
Now we get Dickens, OK? Just pick Mr. Pickwick, remind you of Christmas in a way.
Yeah, Christmas is a winter's day, and I don't think Mr. Pickwick would mind the comparison.
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.
OK, now let's suppose that that conversation took place and we were completely assured that these responses had not as it were being built in,
there wasn't any trickery involved.
You know, canned responses just coming out and supposed conversations of similar levels of sophistication came across quite a range of topics,
not just on poetry, a number of things. The force of Turing's argument here is to say surely.
Surely we would then have to say that this is exhibiting intelligence.
This would be pretty strong evidence. And in the context of 1950, where obviously Turing cannot appeal to achievements in robotics,
for example, or simulation of human behaviour, physical behaviour or anything like that,
this kind of achievement, if if it were to be achieved in verbal response,
would be pretty much a strong evidence of intelligence, as perhaps you could get.
So it's propaganda. It's quite effective.
OK, section three Turing goes onto the machines concerned in the game, and you will see that there is another bit of humour coming in.
We want to allow all sorts of different engineering techniques to be used to create these machines.
However, we wish to exclude from the machines men born in the usual manner.
In other words,
we're not going to treat biological reproduction as an appropriate way of producing a thinking machine because otherwise that would include all of us.
So Turing is obviously pushing towards saying our restriction is going to be digital computers, right?
We don't. We don't want to rule out a machine on the grounds that it's made of one thing rather than another.
We do want to rule out biological organisms.
So what we're going to do is go for digital computers, which of course, is exactly the domain of his 1936 paper.
The idea behind digital computers is that these machines are intended to carry out any operations which could be done by human computer.
That's a clear echo of section nine of the 1936 paper,
where he argues for the Turing machine as a way of encapsulating all the things that a human computer could do.
He then gives an outline of how they work.
He considers some particular cases. He suggests that a digital computer could contain a random element.
You could have a computer with an unlimited store and that has special theoretical interest.
Obviously, Turing machines have an unlimited store, and he alludes to Charles Babbage showing that digital machines needn't be electrical.
They could be mechanical. Charles back Babbage designed the analytical engine.
It was never built. Unfortunately, it's far too complex and expensive.
But the idea of an analytical engine was that showing that a digital computer
could be made in principle as a physical machine rather than a mechanical machine,
rather than an electronic universality of digital computers.
Again, a clear echo of the 1936 paper.
And here, bear in mind that Turing is addressing an audience of probably mainly philosophers and general readers,
not people who would be familiar with the results of his 1936 paper.
So processes in the world are really continuous and indeed chaotic.
And Turing gives an illustration of what we now call the butterfly effect, which was quite prescient in 1950.
But even where processes are continuous, they can usefully be modelled by discrete systems and discrete state machines,
as he describes them, is utterly predictable. 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 behaviour of any discrete state machine, so digital computers are, in a sense, universal.
Again, we've seen his model of the universal Turing machine from 1936.
He's pointing out now that not only can you have a computer that can mimic any digital system and any system of axioms rules, etc. of inference,
but also any continuous system can generally at least be modelled with arbitrary, accurate accuracy by some corresponding digital system.
So because digital computers are universal,
the Imitation Game question reduces to this Let's just fix our attention on one particular digital computer.
See? 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 person right here.
It's it's obvious that the Part B is not meant to be taken by a woman, specifically with the computer pretending to be a woman.
All right. OK, now we come to section six and in section six of the paper, Turing considers and rejects nine different objections to his thesis.
And some of these he treats rather humorously, not terribly seriously.
Some of them he discusses more seriously. But I think he also in doing so makes some significant mistakes, which we will see.
But before he considers the objections, he offers a couple of predictions we'll be coming back to these in a later lecture,
but they're quite significant and I think quite prescient.
I believe this in about 50 years time. OK, about 2000,
it will be possible to programme computers with a storage capacity of about 10 to the nine 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.
OK. So in 2000, would it have been possible to programme a computer with a storage capacity of about a gigabyte to make them
play The Imitation Game so well that the average interrogator will go wrong at 30 percent of the time?
I think actually that's rather a plausible prediction.
I think if artificial intelligence research had focussed on achieving that, I think it would have achieved it.
Not true that it did. But I think it could have. We'll come back to that in a later lecture.
Look at the second one. 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 expected to be.
One will be able to think speak of machines thinking without expecting to be contradicted.
I'm in a more authoritative position to discuss that than most of you, but I will tell you this in 2000,
I think it was quite plausible that one could talk of machines thinking without expecting to be contradicted.
I think now it happens all the time anyway.
That's another thing we'll come back to. But do note that as you go through the paper, those are quite significant predictions and important ones.
OK? 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'm not going to spend long on Turing's discussion of this, which seems somewhat flippant.
Certainly, Turing is not sympathetic to such religious doctrines.
He highlights the absurdity of some religious views, e.g., women don't have souls.
Suppose God gives cells. Why shouldn't he give a soul to a computer?
I mean, if one thought that this was a serious discussion, there is a lot that could be said here.
Turing rather skips over it. I'm going to as well.
I think whatever is significant about that objection can be wrapped up in the problem of consciousness,
which will come to light in their heads in the sand.
Objection again, rather flippant. The consequences of machines thinking would be too dreadful.
Let us hope and believe that they cannot do so.
And Turing is suggesting that this lies behind many people's opposition to the idea of machines thinking they just don't want to think about it,
bury their heads in the sand. Consolation is more appropriate than refutation, perhaps in the transmigration of souls.
Yeah, sure. I think again, Turing is having some fun.
I don't actually think the paper could possibly be published in the journal like mind in its current form today.
It would have had a lot heavier editing for some of this stuff, but it does add to the entertainment of reading it.
OK, number three, we come to the mathematical objection and this is a serious objection.
It's been raised in recent years. Well, John Lucas many years ago now, actually and Roger Penrose, the idea is that results like girdles,
but also, you see, Turing is alluding to other results that we looked at in the last lecture church.
Clearly, Rosser Turing results that demonstrate the limited power of discrete state machines.
And does that show actually that humans have an ability that no discrete machine can because we can run through, for example, the Turing?
That's sorry, the girdle proof. We can see that the girdle formula is true, but the girdle formula cannot be proved by the formal system.
Therefore, we are able to do something that the formal system cannot.
Therefore, the human brain has a power that discrete make state machines cannot.
That's a sketch of the kind of argument that Lucas and Penrose suggest.
So it's interesting that cheering anticipates this. Here you can see a clear reference back to the 1936 paper.
Consider the machine specified as follows Will this machine ever answer yes to any question you can see?
That's a bit like will the machine ever print a zero on the tape?
He knows these proved that you cannot have a general machine that will do that.
But in answer to the question, does that show that these machines are less powerful than the human mind?
Not necessarily, no, because humans have limitations too, and superiority over one particular machine.
I mean, suppose we have some Turing machine implementing some axiomatic system and then we do a girdle on it and find a formula that it cannot prove
that just shows we're superior to that machine in that respect doesn't show we are superior to all machines in all respect or even in one.
Okay, so I'm going to put that to one side, but that is potentially an important objection.
So it's one that has been taken seriously down the years.
The argument from consciousness, I think, is probably the most important objection, and it's where I'm going to suggest Turing goes most wrong.
He quotes from Geoffrey Jefferson's list oration of 1949.
So here is Jefferson saying why computers can't think not until the machine can write a sonnet or
compose a concerto because of thoughts and emotions felt and not by the chance for all of symbols?
Could we agree that machine equals brain that is not only write it, but know that he had written it.
So you can see Jefferson is putting a lot of emphasis on that writing of a sonnet, and Turing is responding to this with his examples of sonnet.
No mechanism could feel and not merely artificially signal an easy contrivance pleasure that it successes grief when it's valves fuse,
be made miserable, be charmed. Be angry or depressed. OK, so you get the idea.
The computer can't genuinely feel anything.
So when the computer produces a sonnet, say it's not doing it through genuine thinking.
Now, Turing's response to this is amusing, but I'm going to suggest dubious.
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 to know that either a machine or a man thinks is to be that particular man.
It is, in fact, the solipsistic point of view. It may be the most logical view to hold, but it makes communication of ideas difficult.
A is liable to believe anything, but B does not.
Meanwhile, B is liable to believe B thinks, but it is not.
Instead of arguing continually over this point, it is usual to have the polite convention that everyone thinks.
OK. Solipsism, by the way, is the theory that I am the only thing that exists in the world, right?
Everything else is a figment of my imagination, including all of you.
So if I'm a solipsistic right, I genuinely think that I am the only thing that's thinking.
And Turing is suggesting that if we follow the logic of Jefferson's objection, we would actually come to the conclusion that solipsism is true.
Now, he then gives his viva voce example.
So I think the previous point will come back to it in a moment I think is highly dubious.
But I think some of what he says about the sonnet example is strong.
So just to remind you, that's the conversation about the sonnet.
You can see it's quite a sophisticated conversation.
What would 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 satisfactory and sustained as in the above passage, I do not think he would describe it as an easy contrivance.
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 solipsistic position.
OK. I think there's a good point there, but I think there's a confusion of two quite distinct lines of thought.
So one of those is that Jefferson is denying the validity of the Turing test because it does not test for genuine consciousness.
And according to Jefferson, genuine consciousness, rather than artificial signalling is necessary for intelligence.
OK, that's one line of thought. A different line of thought is that artificial signalling of apparent emotions
is unworthy of being deemed intelligent because it's an easy contrivance.
OK, so those are two different points. One is saying consciousness is crucial has got to be genuine feeling.
The other one says Easy contrivance isn't enough.
Now Turing runs those together in his response.
And I think his answer to the easy contrivance point is much stronger than his response to the first unconsciousness,
what he'd have been better saying.
And we'll talk about this more in the next two lectures after he gave the sonnet example and others write not just the sonnet,
but examples of similar sophistication of conversation,
he should have said something like this if the answers were satisfactory and sustained, as in the above passage direct quote from him,
then there would be reason to call the machine intelligent, irrespective of whether or not it has genuine feelings.
Intelligent need not require consciousness. That, I think is the way he should have argued.
Obviously, there's a lot more to say about this, so we'll come back to this in, well, the next sector and especially the one after that.
Okay, so we'll put consciousness on one side for now. We then get two arguments from various disabilities.
Again, Turing is obviously being humorous because he includes amongst the disabilities, being kind,
beautiful, friendly, having initiative, having a sense of humour, telling right from wrong making mistakes.
Okay, that's a disability. Maybe fall in love.
Well, maybe that his enjoy strawberries and cream, learn from experience, use words properly, be the subject of its own thought.
Do something really new.
Now, obviously, the limited machines of 1950 couldn't do these, but it requires some argument to show that no machine could allow.
Some of these just seem to take us back to the argument from consciousness.
Okay, I'm being kind, you might say, to be genuinely kind.
Do you actually have to have feeling for the other person or a robot is not kind, even if it does the kinds of things that kind people would do?
Enjoy strawberries and cream? Well, presumably you need to be conscious to do that.
So quite a lot of this just takes us back to that argument when we are actually talking about disabilities, like making a mistake, Turing remarks.
This is a very old complaint. I mean, to say computers can't be intelligent because they can't make mistakes would be very odd.
We normally think of the intelligent person as making fewer mistakes than the unintelligent person.
But also, he points out that you could programme a machine to make errors in the same in a humanlike way, potentially.
But again, it would be odd to say that worst performance makes it more intelligent.
Number six, we come to Lady Lovelace's objection. This can seem quite a strong objection, or it's a very popular one.
But I think Turing deals with this reasonably well.
He quotes Ada Lovelace saying that Charles Babbage's analytical engine has no pretensions to originate anything.
It can do whatever we know how to order it to perform.
So a computer programme essentially just follows orders.
Therefore, it can't be intelligent and you can see there are there are interesting issues raised here.
For example, if we discuss the relation between intelligence and free will.
But on the point about not originating anything, Turing points out that we can often be surprised by the outcome of things.
I mean, it's perfectly possible, for example, to write a computer programme which experiments you can write a computer programme,
which compares different strategies against each other.
So, for example, you could write a computer programme to play a game,
maybe that you've never played before something like three dimensional noughts and crosses or something like that.
Maybe you've never. That but you could write a programme that learns strategies for playing that
simply by trying different strategies and comparing them against each other.
And then at the end of it, you've got a programme that plays the game far, far better than you could yourself.
It's odd to say that it's just doing what it's told. No, it's actually learning.
Now you might say, yeah,
but it's not genuinely learning because the learning mechanism itself is under the control of an algorithm that you have written.
Well, OK. But then if you're going to push this argument, I suspect that it's taking us back to issues about consciousness.
Genuine agency again free will, but apparently tied in with the idea that one needs to be conscious of what one's doing.
And I want to be fair to Ada Lovelace.
She wrote some famous notes on Babbage's analytical engine in virtue of which she's often spoken of as the first computer programmer.
And the quotation from Turing he was he was quoting from Note eight note gee, sorry of her 1842 notes,
but Note A includes this interesting statement the operating mechanism might act upon other things.
Besides, no were object found whose mutual fundamental relations could be expressed by those of the abstract science of operations
and which should be also susceptible of adaptations to the action of the operating notation and mechanism of the engine.
Supposing, for instance, that the fundamental relations of pitched sounds in the science of harmony and
of musical composition was susceptible of such expression and adaptations,
the engine might compose elaborate and scientific pieces of music of any degree of complexity or extent.
So it's a little unfair to Ada Lovelace that because of Turing's paper,
she is very widely known as someone who denied that computers could originate anything when actually more prominently in that document,
she was saying, uh, again.
Very prophetically, the Babbage's analytical engine had the potential to operate in lots of different spheres,
music as well as numbers, and to be creative in the sense of coming out with new compositions.
OK. Just to finish the last few sections of Turing's paper, we get the argument from continuity in the nervous system.
The nervous system is not a discrete state machine. A small error in the information about the size of a nervous impulse impinging
on Neurone may make a large difference to the size of the outgoing impulse.
And again, we he makes the point about how a discrete state machine can mimic a continuous system.
The argument from informality of behaviour,
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. And he points out that this is a fallacy.
And in any case,
it's hard to establish that we're not in fact governed by laws of behaviour and laws of behaviour are not the same as rules of conduct.
OK, rules of conduct tell you what you ought to do.
Laws of behaviour are natural laws or consequences of natural laws, which determine how we do, in fact, behave.
So, for example, many of you will have read section eight of Hume's first enquiry, where he discusses liberty and necessity.
And Hume clearly takes the view that although we don't know what they are,
there are underlying laws of behaviour that we are determined in what we do.
Finally, in this section, we get the argument from extrasensory perception.
This seems very odd. You might. What's that doing there?
Well, first of all, Turing seems to think that the statistical evidence for telepathy and psychic Karnezis and so on is strong, indeed overwhelming.
Most of us now inform people would not think this was true, but a guy called J.B. Rhine at the time was quite influential.
He was doing a lot of experiments, and Hodges, in his biography of Turing, points out that Turing seems to have been impressed with that.
And the sad fact is on either sad or happy, depending on how you look at it, I suppose.
But the evidence simply hasn't stood up very well. I don't think many would say that there is compelling evidence for these phenomena.
But anyway, during thought there was let suppose that there was,
then you can see why cheering might be concerned because if extrasensory perception were possible,
then that's something that a machine probably couldn't mimic. It could mean that we have going into the processing of our conversation forms
of perception that Turing is not going to be able to imitate in his machine.
Just by the way, I've alluded to Hodges biography. It does seem plausible that Turing's great interest in things like spiritualism and
clairvoyance and that kind of thing were influenced by the death of Christopher Morcombe,
his intimate friend when he was very young. I'm thinking about life after death, hoping that the soul continues to exist and so forth.
So it's perhaps not surprising that it has, you know, that it features in in this paper.
The finally, we get on to learning machines where Turing starts off saying,
I have no very convincing arguments of a positive nature to support my views.
The only really satisfactory support that can be given for the view expressed at the beginning of
Section six will be that provided by waiting for the end of the century and then doing the experiment.
So he's now referring back to those predictions that I drew your attention to.
And he's basically saying, Well, I can't prove that what I say is right here.
But wait and see. Well, I think there is a lot to be said for seeing his paper as.
If you like propaganda, largely what he's doing is.
You're saying you may naturally be very disinclined to think that computers can be intelligent?
Let me give you a thought experiment. Suppose they could perform this well, would that not force you to revise your view?
I actually think it would force you to revise your view. I think if computers could do this, general use of language would change.
We would come to call them intelligent and so on. That's my prediction.
Let's wait and see. But it gives a way of addressing the question which takes it away from all these
what he thinks of as irrelevant issues like the theological objection and so on.
And it potentially also takes it away from issues like consciousness, though,
as we've seen, Turing doesn't separate those as much as perhaps he should.
We've seen he's ending with the section on learning machines.
He actually suggests that the way to get a machine that can perform to the desired standard might
be to try to simulate a baby's mind rather than an adult and provide it with the ability to learn.
OK.
This seems frankly very unrealistic, but it's easy for us to say that because we've seen a lot of experience, you know, of artificial intelligence.
We know how difficult it is to learn.
We know how difficult it is to interact with the physical environment, something that babies do very effectively.
They learn huge amounts through their physical senses to get a computer,
to be able to learn in anything like that way so far beyond us and likely to be for some time.
An important point that Turing makes here is that learning machine is highly likely to behave
in ways that its programmers could neither foresee nor understand and also to make mistakes.
So he's bolstering up points he's already made in the paper.
Many people think that a very abstract activity, like the playing of chess might be a good place to start in attempting to match human intelligence.
Chess was indeed seen as a paradigm case for artificial intelligence for many, many years.
But perhaps instead, it's best to provide the machine with the best sense organs that money can buy and then teach it to
understand and speak English so that it could then follow the normal teaching of a child again.
This now seems incredibly naive. General natural language understanding is extraordinarily difficult,
and progress in things like machine translation has tended to come in recent years,
from humungous amounts of data analysed statistically, rather than the kind of formal methods that may initially have seemed more promising.
Okay, on that uncertain note, as I say, the paper ends.
Please make sure you read it carefully before the next lecture.
I hope that what we've covered today will help you to appreciate both its virtues and its some of its vices.
Thank you.