Xref: utzoo talk.philosophy.misc:3901 comp.ai:6563 Path: utzoo!utgpu!news-server.csri.toronto.edu!cs.utexas.edu!uunet!mcsun!ukc!tcdcs!swift.cs.tcd.ie!maths.tcd.ie!ftoomey From: ftoomey@maths.tcd.ie (Fergal Toomey) Newsgroups: talk.philosophy.misc,comp.ai Subject: Re: Why the Chinese Room doesn't convince Message-ID: <1990Apr10.214408.887@maths.tcd.ie> Date: 10 Apr 90 21:44:08 GMT References: <23100@mimsy.umd.edu> <1990Mar19.153959.6113@sjuphil.uucp> <0541@sheol.UUCP> <1990Mar26.155415.21756@sjuphil.uucp> <0556@sheol.UUCP> <1990Apr3.162019.27598@maths.tcd.ie> <1990Apr5.202224.27534@caen.en Organization: Dept. of Maths, Trinity College, Dublin, Ireland. Lines: 126 In article <1990Apr9.063331.15478@cs.umn.edu> hougen@cs.umn.edu (Dean Hougen) writes: >So why has explaining why one won or lost been >proposed (here and elsewhere) as a criterion for understanding chess? >Perhaps it is the psychological impact of imagining a brain-damaged >novice with a list (or, god forbid, a machine) understanding chess. "I >know understanding chess is hard, and if he (it) is playing chess well, >then playing chess well must not be what is meant by understanding chess. >Let's see, what else could it mean to understand chess? ... " We are, in fact, arguing in a very sloppy manner, but this is inevitable. We have no consensus on what understanding is, nor on what (in the example of the chess game) is actually being understood. In presenting my argument I hoped that people would see that the novice+list cannot understand chess within the normal use of the word "understand". I know that if I were placed in the position of the novice, I would not feel that I understood chess. I would not get up after a game and say "Ah! now I understand chess". Dean and some others seem to have got the impression that I don't think that machines are not capable of understanding. I'd like to clarify my position on this. I have chosen not to take sides in the Strong AI debate (that is, the "Minds are just machines vs. Minds are more than just machines" debate) because there is simply not enough evidence to justify either position. The balance of evidence at present seems to indicate that minds *are* just machines made of meat, but alas, the evidence is just not conclusive. In the mean time, I choose to work on the assumption that minds are machines, and that therefore we may be able to build machines which are minds. I assume, therefore, that machines can understand. But I do not feel that behaviour implies understanding. One reason I feel this way is because it is more constructive to study understanding itself than just to say, "Well, if it plays chess, it must understand chess, therefore we don't have to bother working out what understanding is". The Wright brothers could have said, "Well it's very hard to work out what the laws of aerodynamics are, but luckily we don't have to bother with these laws, since we know that if something flys, then it must obey them. Therefore, all we have to do is stick bits of wood and metal together in random ways, throw them up in the air, and if they fly, then they fly." AI researchers would be better off finding out what understanding is, than just saying, "Well, if it passes a Turing test, then it must understand". >The hint-machine will only "be able to" give >hints/explain games, it won't *understand chess*. I don't expect Ken >to follow to this position, but I would ask him to consider how he got >where he is. The same for Fergal. There is no contradiction in my position. In introducing the hint-machine, I *defined* it as a machine which understands chess. >To look at a more real-world example, suppose one of these days I get >up from my desk in the new EE/CSci building, walk out the front doors >and across Washington Avenue to the Health Sciences complex, and spend >some time carefully observing medical diagnosis taking place. I then ask >some of the doctors how they go about making diagnoses. I might just find >what many people who have actually done this sort of thing (in order to >construct expert systems) have found: some experts actually *can't* tell >you how they do what they do. Some, in fact, will make up partially false >explanations in order to cover the fact that they cannot give adequate >explanations! True, it was me who brought in the idea of explanations as a way of testing understanding. But as I pointed out in another article, I did this only for convenience. When faced with a human being, the only way you can look at his algorithms is to ask him to explain what he's doing. The point above merely shows that people are not always able to explain their algorithms. When you have a computer, on the other hand, you can look at its algorithm, so the problem doesn't arise. By the way, if you accept that being able to explain something is neccessary evidence of understanding (which I, repeat, *do not*), then your point above about doctors not being able to explain their behaviour leads to the conclusion that behaviour does not imply understanding, which is my position, not yours! :-) Therefore, I think that you should reject, along with me, the idea that being able to explain something is a neccessary condition for understanding. >For some reason, perhaps the psychological >reason mentioned above, some people have twisted the meaning of the word >'understand' so far that we can now say with a straight face that a >human expert acting as an expert within his own field of expertise >doesn't understand his own field of expertise! Seems we have gone >astray somewhere. Perhaps it is time to give serious consideration to >whether, just perhaps, the novice+list *does* understand chess. Put yourself in the position of the novice. Would you understand chess? The answer must be no. Put yourself in the position of the novice and suppose that you have committed the list to memory. Would you understand chess, in the usual sense of the word? The answer again is no. If you claim that the answer is yes, then I contest that it is you, not I, who has twisted the meaning of the word "understanding" beyond its limits. Note again that I am not saying that machines cannot understand, by definition of the word understanding. I am saying that a particular machine, the novice+list machine, cannot understand, and that its lack of understanding cannot be deduced from its behaviour. >I agree that intelligence is no "trick" and that it cannot be easily >implemented, but the fact that no one has succeeded yet with the full >thing is hardly a proof of this. Getting a machine to play chess the >way people do is probably quite hard, but brute-force may well get us >a World Champion in the form of a machine with the simple addition of >speed. The question is, "Would this champion understand chess?" I >think the answer might just be yes. > >Dean Hougen So artificial intelligence has been in a rut for 50 years. My own feeling is that this is because AI researchers have behaved much like my alternative Wright brothers above. They have simply messed around with a couple of good ideas like neural nets in the hope that they would hit suddenly upon the secret of artificial intelligence. But it would take a long time to build a plane if you knew nothing about aerodynamics; and it will take a long time to build a machine which understands as well as we do, by anybody's definition of understanding, unless we gain an insight into what understanding *is*. Fergal Toomey.