There has been quite a furore over some remarks made by Chomsky at the recent MIT symposium Brains, Minds and Machines; Chomsky apparently criticised researchers in machine learning who use purely statistical methods to produce simulations without addressing the meaning of the behaviour being simulated – there’s a brief account of the discussion in Technology Review. The wider debate was launched when Google’s Director of Research, Peter Norvig issued a response to Chomsky. So far as I can tell the point being made by Chomsky was that applications like Google Translate, which uses a huge corpus of parallel texts to produce equivalents in different languages, do not tell us anything about the way human beings use language.
My first reaction was surprise that anyone would disagree with that. The weakness of translation programmes is that they don’t deal with meanings, whereas human language is all about meanings. Google is more successful than earlier attempts mainly because it uses a much larger database. We always knew this was possible in principle, and that there is no theoretical upper limit to how good these translations can get (in theory we can have a database of everything ever written); it’s just that we (or I, anyway) underestimated how much would be practical and how soon.
As an analogy, we could say it’s like collecting exhaustive data about the movement of heavenly bodies. With big enough tables we could make excellent predictions about eclipses and other developments without it ever dawning on us that the whole thing was in fact about gravity. Norvig reads into Chomsky’s remarks a reassertion of views expressed earlier that ‘statistical’ research methods are no more than ‘butterfly collecting’. It would be a little odd to dismiss the collection of data as not really proper science – but it’s true that we celebrate Newton who set out the law of gravity, and not poor Flamsteed and the other astronomers who supplied the data.
But hang on there. A huge corpus of parallel texts doesn’t tell us anything about the way human beings use language? That can’t be right, can it? Surely it tells us a lot about the way certain words are used, and their interpretation in other languages? Norvig makes the point that all interpretation is probabilistic – we pick out what people most likely meant. So probabilistic models may well enlighten us about how human beings process language. He goes on to point out that there may be several different ways of capturing essentially the same theory, some more useful for some purposes than others: why rule out statistical descriptions?
Hm, I don’t know. Certainly there are times when we have to choose between rival interpretations, but does that make interpretation essentially probabilistic? There are times when we have to choose between two alternative jigsaw pieces, but I wouldn’t say that solving a jigsaw was a statistical matter. Even if we concede that human interpretation of language is probabilistic that glosses over the substantial point that in human beings the probabilistic judgements are about likely meanings, not about likely equivalent sentences. Human language is animated by intentionality, by meaning things: and unfortunately at the moment we have little idea of how intentionality works.
But then, if we don’t know how meaning works, isn’t it possible that it might turn out to be statistical (or probabilistic, or anyway some sort of numerical)? I don’t think it is possible to rule this out. If we had some sort of neural network which was able to do translations, or perhaps talk to us intelligently, we might be tempted to conclude that its inner weightings effectively encoded a set of probabilities about sentences and/or a set of meanings – mightn’t we? And who knows, by examining those weightings might we not finally glean some useful insight into how leaden numbers get transmuted into the gold of semantics?
As I say, I don’t think it’s possible to rule that out – but we know how Google Translate works and it isn’t really anything like that. Norvig wouldn’t claim -would he? – that Google Translate or other programs written on a similar basis display any actual understanding of the sentences they process. So it still seems to me that, whether or not his wider attitudes are well-founded, Chomsky was essentially right.