Turing 2018/6: “Computing Machinery and Intelligence” – Overview of Turing’s 1950 paper

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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.

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I've not corrected it. It should say X prime equals x plus one.

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That's in slide one five two one five three and one five four.

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It previously said X equals x prime plus one, which was the wrong way round.

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This is clearly saying X Prime is the successor of X.

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That was correct. My gloss on it was mistaken. Sorry about that.

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Seems to be fine, Andy. Today we move on from the 1936 paper to the 1950 paper even more famous.

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It's one of the most cited philosophical papers ever published computing, machinery and intelligence.

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It was published in the prominent journal mined in 1950.

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You'll find that there are quite a lot of allusions back to the 1936 paper,

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so watch out for those quite a lot of what Turing says is alluding to results that he had proved then.

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I'm just putting on the slides here some useful books on the philosophy of AI on the Chinese room argument,

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as well as on Turing, will be dealing with cells Chinese room argument next time.

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Some useful collections of papers. This one we've already seen.

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There's a collection that I edited with Andy Clock back in 1996 that was from a conference commemorating Turing.

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And there are seven papers in there that are relevant to the Turing test and also my introduction.

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And there's a book devoted to the Chinese room argument that I mention there.

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Stanford Encyclopaedia of Philosophy is often very useful on philosophical things quite generally,

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and it's got an article on the Turing test and on the Chinese room, and there are some useful web resources.

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Andrew Hodges, who wrote the monumental biography of Alan Turing, has a website devoted to him.

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Lots of good stuff there and a very long paper with some useful stuff.

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I think of more mixed quality, but not all the points made.

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There are ones that I'd agree with, but it's got a lot of scholarly material on the Turing test.

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They're well worth looking at. OK.

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The 1950 paper is perhaps often taken more seriously than it ought to be, and this is a point worth starting with.

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This is a quotation from Robin Gandy I think may be the last thing he ever published.

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This was in our collection in 1996. The 1950 paper was intended not so much as a penetrating contribution to philosophy, but as propaganda.

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He wrote this paper, unlike his mathematical papers, quickly and with enjoyment,

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I can remember him reading aloud to me some of the passages always with a smile, sometimes with a giggle.

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Some of the discussions of the paper loaded with more significance than it was intended to bear there.

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Robin Gandhi was an intimate friend of Turing's.

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He was his Ph.D. student. He was Turing's literary executors of Turing left his papers to Gandhi.

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He also, interestingly ended up at Oxford, where one of the things that he did was to start the maths and philosophy degree.

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Back in 1969, in 1972, modern languages philosophy, modern languages was started in the next degree.

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To be started after that in philosophy was computer science philosophy in 2012.

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So a bit of a legacy then.

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OK, The Imitation Game is Turing's way of reworking the question.

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Can machines think? And this is a bit confusing, a bit odd.

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I proposed to consider the question Can machines think if the meaning of the words machine and thing?

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Could it be found by examining how they commonly used? The answer is to be sought in a statistical survey, but this is absurd.

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Instead, I shall replace the question by another, which is closely related to it, but relatively unambiguous.

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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.

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And we don't standardly think, well, we could go and do a statistical survey and find out what people say.

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But actually the only alternative is to replace it with a completely different question.

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So there's something a little bit odd about Turing's procedure, but let's see where it leads.

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His replacement question is in the context of an imitation game, and he introduces this in the context of a question over identity.

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We have an interrogator in one room who is sending questions to two individuals in two other rooms.

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The questions are being sent in text, so Turing suggests a teletype machine.

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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.

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And here we've got Charles Babbage and Ada Lovelace, who I've taken as my sample man and woman it.

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When the game is played, the interrogator doesn't actually know the identity of the people concerned has no idea who they are.

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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.

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And the interrogators job is to try to work out which is the man, which is the woman.

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But the twist on it is that the man is pretending to be a woman.

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So if, as Turing says, he asks, How long is your hair?

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The man might reply, My hair is shingled, and the longest strands are about nine inches long.

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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.

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I mean, in the modern context, one might ask who won the Premiership this year?

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And the man will respond, Oh, I don't know anything about football. I'll have to ask my boyfriend.

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So you can imagine it could be quite fun.

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I mean, it seems to have its origin in the sort of Victorian parlour game now.

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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.

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So if the interrogator ends up essentially tossing a coin, or suppose you play this game repeatedly with different interrogation?

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It is, and the man scores about 50 per cent, so the interrogator is only able to get him half the time.

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That's pretty much as good as it gets.

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It would be a bit peculiar if the man was able to impersonate a woman better than a woman can represent herself.

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But. So the interrogators in a different room, tones of voice are ruled out because the answers are purely by text, as you see.

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Turing is suggesting a tele printer. And then we get the computer being introduced.

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We now ask what will happen when a machine takes the place of a.

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That is the deceitful man in this game.

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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?

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These questions replace our original can machines think?

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That's again, rather peculiar. They replaced the original question.

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What does that mean, then the machine? The question was can machines think that looks like it's got a yes or no answer?

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Or maybe the answer would be possibly yes. Machines could in principle think, are we really supposed to replace that with the question,

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can a machine play The Imitation Game as well as a man can against a woman?

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That seems a bit peculiar. Moreover, it's not clear exactly what the computer's job is.

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Here is the job to pretend to be a woman, or is the job to pretend to be a human?

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That actually does become clear later in Sections two and five of the paper.

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It becomes obvious that Turing is seeing the computer as trying to imitate a person.

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I mean, he often says a man, but that in 1950, when you say man, you often mean person.

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That's changed considerably. So this is the way the Turing test is normally understood.

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We've still got the interrogator. We've got the teletype communicating to two different rooms, if you like.

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One of them contains a computer running a programme. The other one contains a person could be either man or woman doesn't matter.

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And the computer is trying to impersonate a person.

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Either man or woman doesn't matter. And the result that Turing seems to be hinting at, he doesn't state it very explicitly.

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But this seems to be the drift of his paper that if the interrogator can't reliably distinguish the computer from the human,

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then the computer programme must be judged to be intelligent for thinking that that seems to be where he's going.

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In Section two of the paper, Turing's idea about what he's doing is clarified.

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The interrogators questions can be used to elicit the computer's knowledge about almost any of the fields of human endeavour.

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And he gives some examples we'll see in a moment and notice that the set up has the advantage as he points

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out of drawing a fairly sharp line between the physical and the intellectual capacities of a person.

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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.

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The interrogator doesn't actually see who is responding. All all he gets is the textual responses and has to judge on that basis.

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But as Turing says, those textual responses could cover a wide range of things.

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So here's an illustrative conversation that he gives.

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Please might write me a summit on the subject of the fourth bridge that comes the answer.

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Count me out on this one. I never could write poetry. It seems, may seem a rather strange thing to ask.

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As your first question, please write me a sonnet, not the sort of thing you would expect to happen in an interactive conversation.

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We'll see why Turing gives the example of a sonnet later.

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He's responding to Geoffrey Jefferson at thirty four thousand nine hundred fifty seven to

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seventy thousand seven hundred sixty four poles about 30 seconds and then give his answer,

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other than 5000 621.

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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.

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Do you play chess? Yes. And he gives a very simple chess set up, and after a pause of 15 seconds to educate Mate,

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I conclude that Turing was not particularly expert at chess if he thought it took 15 seconds to work that one out.

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There we go. Yeah, OK.

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An obvious objection to the Turing test. It seems to be biased in favour of human thought, and Turing says may not.

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Machines carry out something which ought to be described as thinking, but is very different from what a human person does.

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And indeed, this seems to be an obvious objection.

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I mean, suppose an alien comes down from the planet Zog and takes place that takes part in this test and.

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The alien is asked this question and comes back with an answer immediately.

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We just know it isn't a human. Certainly not in any sort of normal human.

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Does that mean it's not intelligent? No.

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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.

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And likewise, if you if you ask it, you know, how long is your hair?

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What hair? Maybe the aliens on Zog don't have any hair that wouldn't count against its being intelligent.

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So it seems odd to have a test which depends on mimicking humans.

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Turing's response is that the objection is indeed a very strong one,

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but at least we can say that if nevertheless a machine can be constructed to play The Imitation Game satisfactorily,

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we need not be troubled by this objection. Now again, he doesn't say very explicitly where he's driving here,

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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.

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So if something passes the Turing test, then we are to deem it intelligent.

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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.

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Now I want to just now refer to something later in the paper.

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I mean, I'm generally going in this lecture I'm going through,

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as you see in sequence through the paper to guide your reading of it, and I please do read it before the next lecture.

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I hope you know this will help you to identify the principal points in it.

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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.

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And it concerns the choice of words in a poem. And here is the dialogue.

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So again, we've got this sonnet.

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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,

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which reads, Shall I compare this to a summer's day? Wouldn't a spring day do as well?

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Or better back comes the answer. It wouldn't scan.

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In other words, it would have the wrong rhythm. Shall I compare this to a spring day?

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Not enough syllables. How about a winter's day that would scan?

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All right. Shall I compare it to a winter's day? Yes, but nobody wants to be compared to a winter's day.

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Would you say Mr. Pickwick reminded you of Christmas, then we had an allusion to Shakespeare and a Shakespearean sonnet?

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Now we get Dickens, OK? Just pick Mr. Pickwick, remind you of Christmas in a way.

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Yeah, Christmas is a winter's day, and I don't think Mr. Pickwick would mind the comparison.

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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.

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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,

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there wasn't any trickery involved.

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You know, canned responses just coming out and supposed conversations of similar levels of sophistication came across quite a range of topics,

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not just on poetry, a number of things. The force of Turing's argument here is to say surely.

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Surely we would then have to say that this is exhibiting intelligence.

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This would be pretty strong evidence. And in the context of 1950, where obviously Turing cannot appeal to achievements in robotics,

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for example, or simulation of human behaviour, physical behaviour or anything like that,

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this kind of achievement, if if it were to be achieved in verbal response,

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would be pretty much a strong evidence of intelligence, as perhaps you could get.

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So it's propaganda. It's quite effective.

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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.

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We want to allow all sorts of different engineering techniques to be used to create these machines.

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However, we wish to exclude from the machines men born in the usual manner.

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In other words,

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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.

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So Turing is obviously pushing towards saying our restriction is going to be digital computers, right?

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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.

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We do want to rule out biological organisms.

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So what we're going to do is go for digital computers, which of course, is exactly the domain of his 1936 paper.

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The idea behind digital computers is that these machines are intended to carry out any operations which could be done by human computer.

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That's a clear echo of section nine of the 1936 paper,

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where he argues for the Turing machine as a way of encapsulating all the things that a human computer could do.

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He then gives an outline of how they work.

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He considers some particular cases. He suggests that a digital computer could contain a random element.

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You could have a computer with an unlimited store and that has special theoretical interest.

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Obviously, Turing machines have an unlimited store, and he alludes to Charles Babbage showing that digital machines needn't be electrical.

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They could be mechanical. Charles back Babbage designed the analytical engine.

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It was never built. Unfortunately, it's far too complex and expensive.

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But the idea of an analytical engine was that showing that a digital computer

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could be made in principle as a physical machine rather than a mechanical machine,

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rather than an electronic universality of digital computers.

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Again, a clear echo of the 1936 paper.

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And here, bear in mind that Turing is addressing an audience of probably mainly philosophers and general readers,

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not people who would be familiar with the results of his 1936 paper.

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So processes in the world are really continuous and indeed chaotic.

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And Turing gives an illustration of what we now call the butterfly effect, which was quite prescient in 1950.

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But even where processes are continuous, they can usefully be modelled by discrete systems and discrete state machines,

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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,

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provided it could be carried out sufficiently quickly.

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The digital computer could mimic the behaviour of any discrete state machine, so digital computers are, in a sense, universal.

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Again, we've seen his model of the universal Turing machine from 1936.

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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,

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but also any continuous system can generally at least be modelled with arbitrary, accurate accuracy by some corresponding digital system.

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So because digital computers are universal,

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the Imitation Game question reduces to this Let's just fix our attention on one particular digital computer.

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See? Is it true that by modifying this computer to have an adequate storage,

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suitably increasing its speed of action and providing it with an appropriate programme,

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C can be made to play satisfactorily the part of a in The Imitation Game.

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The part of B being taken by a man person right here.

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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.

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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.

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And some of these he treats rather humorously, not terribly seriously.

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Some of them he discusses more seriously. But I think he also in doing so makes some significant mistakes, which we will see.

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But before he considers the objections, he offers a couple of predictions we'll be coming back to these in a later lecture,

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but they're quite significant and I think quite prescient.

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I believe this in about 50 years time. OK, about 2000,

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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

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an average interrogator will not have more than 70 per cent chance of making the right identification after five minutes of questioning.

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OK. So in 2000, would it have been possible to programme a computer with a storage capacity of about a gigabyte to make them

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play The Imitation Game so well that the average interrogator will go wrong at 30 percent of the time?

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I think actually that's rather a plausible prediction.

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I think if artificial intelligence research had focussed on achieving that, I think it would have achieved it.

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Not true that it did. But I think it could have. We'll come back to that in a later lecture.

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Look at the second one. The original question? Can machines think, I believe, to be too meaningless to deserve discussion?

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Nevertheless, I believe that at the end of the century,

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the use of words and general educated opinion will have altered so much that one will be expected to be.

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One will be able to think speak of machines thinking without expecting to be contradicted.

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I'm in a more authoritative position to discuss that than most of you, but I will tell you this in 2000,

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I think it was quite plausible that one could talk of machines thinking without expecting to be contradicted.

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I think now it happens all the time anyway.

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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.

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OK? The theological objection thinking is a function of man's immortal soul.

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God has given an immortal soul to every man and woman, but not to any other animal or to machines.

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Hence, no animal or machine can think. I'm not going to spend long on Turing's discussion of this, which seems somewhat flippant.

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Certainly, Turing is not sympathetic to such religious doctrines.

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He highlights the absurdity of some religious views, e.g., women don't have souls.

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Suppose God gives cells. Why shouldn't he give a soul to a computer?

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I mean, if one thought that this was a serious discussion, there is a lot that could be said here.

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Turing rather skips over it. I'm going to as well.

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I think whatever is significant about that objection can be wrapped up in the problem of consciousness,

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which will come to light in their heads in the sand.

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Objection again, rather flippant. The consequences of machines thinking would be too dreadful.

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Let us hope and believe that they cannot do so.

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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,

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bury their heads in the sand. Consolation is more appropriate than refutation, perhaps in the transmigration of souls.

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Yeah, sure. I think again, Turing is having some fun.

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I don't actually think the paper could possibly be published in the journal like mind in its current form today.

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It would have had a lot heavier editing for some of this stuff, but it does add to the entertainment of reading it.

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OK, number three, we come to the mathematical objection and this is a serious objection.

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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,

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but also, you see, Turing is alluding to other results that we looked at in the last lecture church.

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Clearly, Rosser Turing results that demonstrate the limited power of discrete state machines.

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And does that show actually that humans have an ability that no discrete machine can because we can run through, for example, the Turing?

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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.

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Therefore, we are able to do something that the formal system cannot.

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Therefore, the human brain has a power that discrete make state machines cannot.

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That's a sketch of the kind of argument that Lucas and Penrose suggest.

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So it's interesting that cheering anticipates this. Here you can see a clear reference back to the 1936 paper.

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Consider the machine specified as follows Will this machine ever answer yes to any question you can see?

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That's a bit like will the machine ever print a zero on the tape?

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He knows these proved that you cannot have a general machine that will do that.

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But in answer to the question, does that show that these machines are less powerful than the human mind?

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Not necessarily, no, because humans have limitations too, and superiority over one particular machine.

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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

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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.

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Okay, so I'm going to put that to one side, but that is potentially an important objection.

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So it's one that has been taken seriously down the years.

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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.

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He quotes from Geoffrey Jefferson's list oration of 1949.

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So here is Jefferson saying why computers can't think not until the machine can write a sonnet or

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compose a concerto because of thoughts and emotions felt and not by the chance for all of symbols?

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Could we agree that machine equals brain that is not only write it, but know that he had written it.

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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.

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No mechanism could feel and not merely artificially signal an easy contrivance pleasure that it successes grief when it's valves fuse,

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be made miserable, be charmed. Be angry or depressed. OK, so you get the idea.

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The computer can't genuinely feel anything.

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So when the computer produces a sonnet, say it's not doing it through genuine thinking.

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Now, Turing's response to this is amusing, but I'm going to suggest dubious.

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This argument appears to be a denial of the validity of our test, according to the most extreme form of this view.

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The only way to know that either a machine or a man thinks is to be that particular man.

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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.

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A is liable to believe anything, but B does not.

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Meanwhile, B is liable to believe B thinks, but it is not.

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Instead of arguing continually over this point, it is usual to have the polite convention that everyone thinks.

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OK. Solipsism, by the way, is the theory that I am the only thing that exists in the world, right?

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Everything else is a figment of my imagination, including all of you.

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So if I'm a solipsistic right, I genuinely think that I am the only thing that's thinking.

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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.

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Now, he then gives his viva voce example.

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So I think the previous point will come back to it in a moment I think is highly dubious.

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But I think some of what he says about the sonnet example is strong.

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So just to remind you, that's the conversation about the sonnet.

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You can see it's quite a sophisticated conversation.

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What would Jefferson say if the sonnet writing machine was able to answer like this in the viva voce?

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I do not know whether he would regard the machine as merely artificially signalling these answers.

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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.

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In short, then, I think that most of those who support the argument from consciousness could be

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persuaded to abandon it rather than be forced into the solipsistic position.

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OK. I think there's a good point there, but I think there's a confusion of two quite distinct lines of thought.

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So one of those is that Jefferson is denying the validity of the Turing test because it does not test for genuine consciousness.

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And according to Jefferson, genuine consciousness, rather than artificial signalling is necessary for intelligence.

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OK, that's one line of thought. A different line of thought is that artificial signalling of apparent emotions

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is unworthy of being deemed intelligent because it's an easy contrivance.

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OK, so those are two different points. One is saying consciousness is crucial has got to be genuine feeling.

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The other one says Easy contrivance isn't enough.

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Now Turing runs those together in his response.

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And I think his answer to the easy contrivance point is much stronger than his response to the first unconsciousness,

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what he'd have been better saying.

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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,

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but examples of similar sophistication of conversation,

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he should have said something like this if the answers were satisfactory and sustained, as in the above passage direct quote from him,

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then there would be reason to call the machine intelligent, irrespective of whether or not it has genuine feelings.

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Intelligent need not require consciousness. That, I think is the way he should have argued.

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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.

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Okay, so we'll put consciousness on one side for now. We then get two arguments from various disabilities.

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Again, Turing is obviously being humorous because he includes amongst the disabilities, being kind,

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beautiful, friendly, having initiative, having a sense of humour, telling right from wrong making mistakes.

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Okay, that's a disability. Maybe fall in love.

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Well, maybe that his enjoy strawberries and cream, learn from experience, use words properly, be the subject of its own thought.

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Do something really new.

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Now, obviously, the limited machines of 1950 couldn't do these, but it requires some argument to show that no machine could allow.

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Some of these just seem to take us back to the argument from consciousness.

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Okay, I'm being kind, you might say, to be genuinely kind.

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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?

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Enjoy strawberries and cream? Well, presumably you need to be conscious to do that.

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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.

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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.

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We normally think of the intelligent person as making fewer mistakes than the unintelligent person.

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But also, he points out that you could programme a machine to make errors in the same in a humanlike way, potentially.

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But again, it would be odd to say that worst performance makes it more intelligent.

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Number six, we come to Lady Lovelace's objection. This can seem quite a strong objection, or it's a very popular one.

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But I think Turing deals with this reasonably well.

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He quotes Ada Lovelace saying that Charles Babbage's analytical engine has no pretensions to originate anything.

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It can do whatever we know how to order it to perform.

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So a computer programme essentially just follows orders.

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Therefore, it can't be intelligent and you can see there are there are interesting issues raised here.

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For example, if we discuss the relation between intelligence and free will.

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But on the point about not originating anything, Turing points out that we can often be surprised by the outcome of things.

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I mean, it's perfectly possible, for example, to write a computer programme which experiments you can write a computer programme,

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which compares different strategies against each other.

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So, for example, you could write a computer programme to play a game,

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maybe that you've never played before something like three dimensional noughts and crosses or something like that.

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Maybe you've never. That but you could write a programme that learns strategies for playing that

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simply by trying different strategies and comparing them against each other.

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And then at the end of it, you've got a programme that plays the game far, far better than you could yourself.

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It's odd to say that it's just doing what it's told. No, it's actually learning.

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Now you might say, yeah,

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but it's not genuinely learning because the learning mechanism itself is under the control of an algorithm that you have written.

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Well, OK. But then if you're going to push this argument, I suspect that it's taking us back to issues about consciousness.

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Genuine agency again free will, but apparently tied in with the idea that one needs to be conscious of what one's doing.

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And I want to be fair to Ada Lovelace.

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She wrote some famous notes on Babbage's analytical engine in virtue of which she's often spoken of as the first computer programmer.

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And the quotation from Turing he was he was quoting from Note eight note gee, sorry of her 1842 notes,

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but Note A includes this interesting statement the operating mechanism might act upon other things.

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Besides, no were object found whose mutual fundamental relations could be expressed by those of the abstract science of operations

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and which should be also susceptible of adaptations to the action of the operating notation and mechanism of the engine.

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Supposing, for instance, that the fundamental relations of pitched sounds in the science of harmony and

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of musical composition was susceptible of such expression and adaptations,

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the engine might compose elaborate and scientific pieces of music of any degree of complexity or extent.

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So it's a little unfair to Ada Lovelace that because of Turing's paper,

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she is very widely known as someone who denied that computers could originate anything when actually more prominently in that document,

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she was saying, uh, again.

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Very prophetically, the Babbage's analytical engine had the potential to operate in lots of different spheres,

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music as well as numbers, and to be creative in the sense of coming out with new compositions.

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OK. Just to finish the last few sections of Turing's paper, we get the argument from continuity in the nervous system.

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The nervous system is not a discrete state machine. A small error in the information about the size of a nervous impulse impinging

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on Neurone may make a large difference to the size of the outgoing impulse.

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And again, we he makes the point about how a discrete state machine can mimic a continuous system.

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The argument from informality of behaviour,

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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.

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But there are no such rules. So men cannot be machines. And he points out that this is a fallacy.

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And in any case,

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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.

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OK, rules of conduct tell you what you ought to do.

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Laws of behaviour are natural laws or consequences of natural laws, which determine how we do, in fact, behave.

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So, for example, many of you will have read section eight of Hume's first enquiry, where he discusses liberty and necessity.

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And Hume clearly takes the view that although we don't know what they are,

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there are underlying laws of behaviour that we are determined in what we do.

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Finally, in this section, we get the argument from extrasensory perception.

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This seems very odd. You might. What's that doing there?

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Well, first of all, Turing seems to think that the statistical evidence for telepathy and psychic Karnezis and so on is strong, indeed overwhelming.

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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.

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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.

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And the sad fact is on either sad or happy, depending on how you look at it, I suppose.

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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.

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But anyway, during thought there was let suppose that there was,

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then you can see why cheering might be concerned because if extrasensory perception were possible,

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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

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of perception that Turing is not going to be able to imitate in his machine.

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Just by the way, I've alluded to Hodges biography. It does seem plausible that Turing's great interest in things like spiritualism and

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clairvoyance and that kind of thing were influenced by the death of Christopher Morcombe,

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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.

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So it's perhaps not surprising that it has, you know, that it features in in this paper.

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The finally, we get on to learning machines where Turing starts off saying,

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I have no very convincing arguments of a positive nature to support my views.

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The only really satisfactory support that can be given for the view expressed at the beginning of

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Section six will be that provided by waiting for the end of the century and then doing the experiment.

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So he's now referring back to those predictions that I drew your attention to.

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And he's basically saying, Well, I can't prove that what I say is right here.

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But wait and see. Well, I think there is a lot to be said for seeing his paper as.

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If you like propaganda, largely what he's doing is.

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You're saying you may naturally be very disinclined to think that computers can be intelligent?

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Let me give you a thought experiment. Suppose they could perform this well, would that not force you to revise your view?

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I actually think it would force you to revise your view. I think if computers could do this, general use of language would change.

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We would come to call them intelligent and so on. That's my prediction.

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Let's wait and see. But it gives a way of addressing the question which takes it away from all these

388
00:47:40,850 --> 00:47:46,010
what he thinks of as irrelevant issues like the theological objection and so on.

389
00:47:46,010 --> 00:47:50,120
And it potentially also takes it away from issues like consciousness, though,

390
00:47:50,120 --> 00:47:58,430
as we've seen, Turing doesn't separate those as much as perhaps he should.

391
00:47:58,430 --> 00:48:02,990
We've seen he's ending with the section on learning machines.

392
00:48:02,990 --> 00:48:09,960
He actually suggests that the way to get a machine that can perform to the desired standard might

393
00:48:09,960 --> 00:48:16,130
be to try to simulate a baby's mind rather than an adult and provide it with the ability to learn.

394
00:48:16,130 --> 00:48:17,060
OK.

395
00:48:17,060 --> 00:48:27,410
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.

396
00:48:27,410 --> 00:48:29,600
We know how difficult it is to learn.

397
00:48:29,600 --> 00:48:36,020
We know how difficult it is to interact with the physical environment, something that babies do very effectively.

398
00:48:36,020 --> 00:48:42,950
They learn huge amounts through their physical senses to get a computer,

399
00:48:42,950 --> 00:48:51,710
to be able to learn in anything like that way so far beyond us and likely to be for some time.

400
00:48:51,710 --> 00:48:55,820
An important point that Turing makes here is that learning machine is highly likely to behave

401
00:48:55,820 --> 00:49:00,890
in ways that its programmers could neither foresee nor understand and also to make mistakes.

402
00:49:00,890 --> 00:49:06,680
So he's bolstering up points he's already made in the paper.

403
00:49:06,680 --> 00:49:15,260
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.

404
00:49:15,260 --> 00:49:23,840
Chess was indeed seen as a paradigm case for artificial intelligence for many, many years.

405
00:49:23,840 --> 00:49:30,620
But perhaps instead, it's best to provide the machine with the best sense organs that money can buy and then teach it to

406
00:49:30,620 --> 00:49:36,530
understand and speak English so that it could then follow the normal teaching of a child again.

407
00:49:36,530 --> 00:49:43,400
This now seems incredibly naive. General natural language understanding is extraordinarily difficult,

408
00:49:43,400 --> 00:49:48,650
and progress in things like machine translation has tended to come in recent years,

409
00:49:48,650 --> 00:50:00,720
from humungous amounts of data analysed statistically, rather than the kind of formal methods that may initially have seemed more promising.

410
00:50:00,720 --> 00:50:04,850
Okay, on that uncertain note, as I say, the paper ends.

411
00:50:04,850 --> 00:50:10,160
Please make sure you read it carefully before the next lecture.

412
00:50:10,160 --> 00:50:18,920
I hope that what we've covered today will help you to appreciate both its virtues and its some of its vices.

413
00:50:18,920 --> 00:50:23,543
Thank you.