I wanted to register a quick reply to some of the comments on last week's post "The question is : are you dumber than a rat?" In the comments there, and in posts on other blogs, our research program has been accused of intelligent nihilism. By one such characterization, our position is that "we don't how the brain could give rise to a particular type of behavior, so humans must not be capable of it." Though I think the label is quite witty -- and would love to have badges made for the lab! -- I think this misrepresents our stance rather badly ; our argument is that many of the properties that linguists have attributed to language are either empty theoretical constructs (hypotheses that are not supported by the empirical evidence) or are conceptually confused (and have been shown to be so; by Wittgenstein, Quine and many others). We are not denying that language -- and linguistic behavior -- are complex; rather, we are rejecting a particular stance towards language that we think is theoretically and empirically vacuous. This does not lead us to nihilism, but rather to a different conception of language and how language is learned.
In any case, the comments on last week's post prove to be fertile ground for discussion, so I've posted them (in pared down fashion) along with a brief response. The full comment thread can be found at the original post.
"One more time for the road: there are some simple learning models that can (maybe) account for learning concrete nouns. I’ll even give you some concrete adjectives like blue. I’m not sure whether that counts as complex linguistic behavior, but it certainly isn’t “much of complex linguistic behavior.” It’s *certainly* not what motivates Chomsky’s or Pinker’s work.
This is a little like saying you don’t need all that fancy quantum mechanics to explain perfect spheres moving in a vacuum — classical mechanics will do just fine. That’s essentially true, but it misses the point. If you’ve got a “simple learning model” that can account for things like verbs and quantifiers, let’s see it."
And then a follow-up:
"I’m sorry, but there is no model of general learning that captures human language. For example, if you look at the best speech recognition systems, as when you phone the bank and the “lady” apologizes because she could not understand that and would you please say something or hold for the operator, it is via a model of mapping acoustic patterns onto pre-determined lookup tables; albeit in a probabilistic, fuzzy way.
Sure there are teeny models for some horribly obvious relations in the world and in some speech tokens; but beyond that all of general learning is just a promissory note. Of COURSE parts of language interface with other cognitive systems and of COURSE they rely on perception. But equally, this is not enough, as a striking lack of talking rats might suggest.
In the end I care about which theory makes the better predictions – not for learning simple word meanings, but for accounting for the organization of the core grammatical properties of language like constituency, categories, recursion and systematicity."
The question I would pose is : How does assuming that semantics and "syntax" are somehow "innate" explain anything?
To date, the output of both Chomsky and Pinker has been a great deal of rhetorical flourish tacked on to bad faith arguments, many of which violate the most basic principles of scientific reasoning. I'm not sure what motivates their contemporary research program or those of their adherents; at times, I'm tempted to think that it's one of the most brilliant academic Ponzi schemes to be mounted in modern times.
Unfortunately, the usual response -- and indeed both of your responses -- are illustrative of a dubious line of reasoning that far too often rears its head on that side of the debate. The response, of course, is never to list the great empirical discoveries of Chomsky or Pinker or linguistic nativism at large. Instead, it is to argue that because an alternative theory doesn't explain everything, it must be far worse than a theory that explains nothing. The hope seems to be that the finer details of this logic will get lost amidst the scuffle. (That this is the kind of reasoning used is not surprising; as I mentioned in "But Science Doesn't Work That Way," the logic underpinning Miller and Chomsky (1963) is similar; compare "we haven't got one model working, therefore it is categorically impossible for any such model to work" to "these models haven't explained everything yet, which means they never will").
The aims of our research program are straightforward : Ramscar's models start out with basic perceptual representations, and explain and predict some very puzzling aspects of the way nouns and adjectives are learned. They also predict previously unobserved phenomena. I find this interesting. I also find little reason to believe that these kinds of models couldn't be productively applied to a much broader range of linguistic phenomena.
Compare the concrete models in Ramscar's papers, and the concrete psychological predictions they make, to Pinker's "Words and Rules" theory -- perhaps the most obvious example of linguistic theory as intelligent design. When it was first put forth, the theory was that "only irregulars are stored" and that regulars were computed by rules. Then, when it was clear that this wouldn't allow the "model" (which has no implementational detail whatsoever) to account for the true scope of regular data, bing! suddenly some regulars -- just enough to fit the data -- were allowed to be stored. Of course, this has had the handy effect of making the model unfalsifiable; it simply incorporates whatever the latest learning model says it has to, plus a rule that is somehow supposed to "explain" everything else. Each time it can be shown that another aspect of how inflection works is better fit by a learning model, the story simply switches to how there are still "phenomena that haven't been accounted for," and the claim is made that somehow (somewhere) this counts as evidence for hardwired rules. Of course, in the Pinker model, these rules have no computational or representational properties other than those that are immediately convenient; Pinker is, of course, the ultimate intelligent designer of his theories.
Is this, I wonder, to be our preferred model of "science"?
As for "the core grammatical properties of language like constituency, categories, recursion and systematicity" -- these are descriptive hypotheses about the way language works, not actual (demonstrable) properties of language. The history of the last 50 years of linguistics and psychology is that, like Pinker's "rules," "constituency, categories, recursion and systematicity" are fun buzz-words to to type into an argument, but Lord help anyone who has to actually cash out what they mean or how they work; these theoretical constructs hide a horrible mess of confused intuitions that don't seem to fit with how people actually process language at all.
What does it even mean to believe in "constituency, categories, recursion and systematicity" anyway? Geoff Pullum and Barbara Scholz have an amusing (and quite brilliant) paper about systematicity claims, that points out that most claims about systematicity are neither well defined, nor even -- dare I say -- systematic. Recursion is a property of one way of modeling language, but it begs a number of questions, not the least of which is how 'categorical' language really is. Consider, for starters, the observable patterns of how words distribute in natural language. These distributional patterns make clear that there are no naturally occurring categories. To make a grammatical category meaningful, you would need to be able to enumerate a set of rules that applied (i.e., generalized) across every word in it, but the linguistic data show these kinds of categories are little more than useful fictions; indeed, much of the careful analysis that has been done in corpus linguistics shows (quite plainly) that such rules simply don't exist. Positing these kinds of linguistic categories is a useful shorthand when talking about language, but I think it's a mistake to forget that what they actually amount to is a kind of theoretical squinting.
All of which leads me into the most frustrating part about all of this -- which is that most researchers who want to claim that language depends on "constituency, categories, recursion and systematicity," prefer to ignore the fact that these are such vague notions that no one can actually tell you what "constituency, categories, recursion and systematicity" actually are.
Are we supposed to have faith that someday, someone out there will figure it all out for us?
The problem with faith-based linguistics, is that it's about as friendly to open scientific inquiry as the inquisition, and people who take the faith-based approach spend a lot of time tuning out (or shouting over) the 'noise' of reasonable dissent. I suppose it's easier than figuring out what "constituency, categories, recursion and systematicity" are, or whether these ideas even make sense.
Pullum, Geoffrey K., & Scholz, Barbara C. (2010). Recursion and the infinitude claim. In Harry van der Hulst (ed.), Recursion in Human Language (Studies in Generative Grammar 104), 113-138 DOI: 10.1515/9783110219258.111
Pullum, Geoffrey K., & Scholz, Barbara C. (2007). Systematicity and natural language syntax. Croatian Journal of Philosophy, 7 (21), 375-402
Pullum, G., & Rawlins, K. (2007). Argument or no argument? Linguistics and Philosophy, 30 (2), 277-287 DOI: 10.1007/s10988-007-9013-y
Gross, M. (1979). On the Failure of Generative Grammar. Language, 55 (4) DOI: 10.2307/412748
Culicover, P. (1999) Syntactic Nuts: Hard Cases in Syntax (Oxford University Press)
A Mess of Clarifications
"If you think the Chomskyan model is like a spreadsheet, the Ramscar model like a search engine, or even if you think in terms of neural nets, for now these are all just variants of computer programs. I don’t see the paradigm shift in comparing your notions of language to computer program A vs program B."
If you want a complete answer to this, you should read my post on this subject and the original papers, Ramscar, Yarlett, Dye, Denny & Thorpe (2010) and Ramscar (2010). I think you would be hard-pressed to conflate the two 'paradigms,' particularly if you read the discussion section in Ramscar et al. But for now, here's a brief reply : While both of these are computational metaphors of mind, they suggest very different things about how humans process information. A spreadsheet rigidly structures the information it's given according to a strict, rule-based program; a search engine is probabilistic and discovers structure within its environment. To bring this back to language : Chomsky argues that we have sophisticated preprogrammed mechanisms for learning and processing language, and that children use this hardwired template to impose structure on verbal input ; by contrast, Ramscar suggests that that structure already exists in the available linguistic information (and our environments) and that children use domain-general learning mechanisms to discover it. I'm not sure how you can argue that imposing structure and discovering structure are the same thing; that would be a funny sort of language game.
"Mo’s argument is that what you can learn is constrained by the representations you have. I’m not sure which part of that computational “metaphor” is out of “date”. Are you arguing that you can have a learning theory that doesn’t have representations? Certainly all the Ramscar models have representations (a perceptual representation is still a representation), and it’s hard to imagine what such a model would look like. Or are you arguing that you have model that can learn *anything* regardless of the representations it uses? For instance, it could learn differential equations entirely in terms of colors. That’d be one hell of a model and I’d like to see it!"
Representations have to be learned either by the individual or by the species, via evolution. We have a good idea of how the mechanisms that give rise to perceptual representations have evolved. These are different in kind from the made-up representations that populate Chomsky's fantasy world of linguistic perfection (which, as far as I can tell, change their fundamental character at least once a decade -- no mean evolutionary trick!) I certainly think that what you learn is constrained by the representations you have ; that's why I think that understanding has to be probabilistic.