Reading about Noam Chomsky vs AI bros and/or rationalists feels like
jumping into the middle of a Godzilla vs Mothra movie. Like, I
think I’m supposed to be rooting for Godzilla to win, because
he’s cooler and theoretically he’s on our side this time. But I’m not
totally sure.
He makes it impossible to ignore the fact that he, too, is a big,
grandiose weirdo who can’t resist commenting outside of the domain of
his expertise. Look at how this article begins:
Chomsky [is] one of the most esteemed public intellectuals of all
time, whose intellectual stature has been compared to that of Galileo,
Newton, and Descartes
I know people hold him in high regard but that’s a ludicrous
statement.
I think the linguistics people feel defensive about the LLM
situation. Over the past 10 years or so the AI bros have been achieving
mind-blowing empirical results that the linguists not only never stood a
chance of achieving, but which the majority of them still don’t
understand at all.
I understand the criticism that the AI bros are just hitting a pile
of data with a giant math hammer and that this approach feels lacking,
but I think that criticism would be a lot more valid coming from someone
who actually understands how the giant math hammer works.
The only people who dismiss the the math so blithely are the people
who don’t get it, and I am certain that Noam Chomsky has no idea at all
how any of this stuff works. That’s why he talks at great length about
linguistics and not at all about the machine learning techniques he’s
dismissing.
IMO Chomsky will probably be regarded closer to Freud than to Newton. He did do a lot of good pioneering work basically creating his field but there's some weird stuff mixed in with good ideas. No one can get it all right the first time.
Disclaimer: am AI bro, read some linguistics and Chomsky stuff during undergrad but grad school has destroyed any knowledge I had about any other field.
The important point is that comparing Chomsky to Isaac Newton is not just wrong, it's *insane.* It's not a sufficiently respectable idea to be worth offering alternatives to.
As a disclaimer: he takes for granted the notion of “impossible languages” and the fact that current machines cannot recognize them I think? I had to google that then quickly got bored, so I don’t pretend to understand what seems to be the crux of his argument.
That being said I want to point out:
1. There’s almost a meme in “we don’t even understand what neural networks do!” and practitioners answering “well *you* don’t but *we* do”; but, it seems mostly due to a different take on the word “understand”, and in fact, there is a lot of work being done on understanding what those models do (in some sense of “understanding”) and it’s still ongoing
2. It is in fact the doxa of what Chomsky calls “engineering” circles that learning (the “learning” of “machine learning”) trumps hand crafted rules from our understanding of the domain
3. So as much as the field heavily uses metaphors and takes inspiration from e.g. biological sciences, it *actively* keeps some distance from the domains it applies it models, prefering indeed focusing on what Chomsky calls “performance”
What I’m trying to say is I don’t think his premises are controversial to the people who activelly work in and understand the “AI” / machine learning / whatever field. What might be is his argument that for “AI” to do the kind of things we want it to do (or believe it already does) the field needs more of what *he does*, not necessarily less of what the practitioners are currently doing.
On that, there’s a parallel with mathematicians dismissing computer based proofs of theorems that explore a huge amount of distinct cases: “good to know that the theorem holds, but what we’re interested in really is a deeper understanding of why it does, and the underlying mechanism that makes it so for so many seemingly different cases”.
[I want to take AlphaGo as an example of the distinction I understand him making between engineering performance and science. It’s a remarkable achievement by all accounts, because it can play better and beat humans at Go. Looking at it play even helps humans learn new strategies. But it doesn’t get us that much better at grasping the underlying mechanisms hidden behind the rules of Go, or at devising those strategies.]
So in that sense I think he’s warranted in his criticism, because it doesn’t require a deep understanding of what the field is producing, but a simple fair observation on what the field is trying to achieve in the first place.
> he takes for granted the notion of “impossible languages” and the fact that current machines cannot recognize them I think?
Isn't it the opposite? He talks about constructed languages humans can't learn (I think relying on linear order or nearness or something) vs. constructed languages that they can (I think it was using some heirarchical principles).
Transformers learn approximations of either about equally well, so don't tell us much about human linguistic cognition in this view. Humans actually can learn the former type too but to a limited extent: in fMRI studies humans use parts of the brain involved in slower puzzle solving tasks when dealing with these constructed "impossible" languages rather than parts that light up in both real natural human languages and "non-impossible" constructed languages that mimic them.
I’m sure you’re right and I misunderstood. I have a mental note to look up the topic and read the OP again later, because that whole chain of argument flew miles over my head. Full disclosure: I don’t know shit about shit.
Also I’m already in the middle of reading seven long ass blog posts on historical sparta versus its portrayal in pop culture because of this subreddit, a topic that interests me roughly as much as linguistics (not at all), so thanks a lot I guess
His criticism *can't* be warranted because he doesn't know enough to be able to make the intelligent version of that criticism. It's a broken clock thing.
And even the intelligent version is misbegotten. What computational technology (e.g. alphago) reveals is that the "manual" way of thinking - working through individual moves in your mind - is an inappropriate level of abstraction for *truly* understanding how the game works. The person who wins the game isn't alphago and it isn't the human opponent, *it's the person who programmed alphago*.
The computer proofs thing is an excellent example of this. In the (probably very near) future there will two kinds of mathematicians: mathematicians who embrace computer proofs, and mathematicians who are irrelevant.
I'm not sure that's necessarily true. For applications of mathematics, sure I can see that being the case. But in terms of pure mathematics it seems to me the whole point of it is solving problems that don't really have any application just because they're interesting or 'beautiful'. In that case using computers just seems pointless, like computers can play chess now but that doesn't mean people are going to stop playing and certainly no one would want two computer programs to play each other
It's true because of incentives of academia. You make your career as a mathematician - in "pure" math or otherwise - by developing new proofs. The people who use computers to aid in proving things are going to be much, much more productive than the people who don't. So the people who don't use computers won't be able to make careers, and they'll be left behind.
There's a social component to it also. The way that proofs have traditionally been done in the past is inefficient and open to mistakes. Writing proofs like software instead is a much more efficient, maintainable, and clear process; it's actually *socially* more effective, which is another reason that productive people will prefer it and everyone else will be ignored.
People will undoubtedly still do proofs entirely by hand for exercise and for fun, of course. But career mathematicians generally won't do it in their real work.
I'm a mathematician and this is WAY too optimistic about the future of computer proofs.
"Developing new proofs" is not really the main point of doing research mathematics, it's a process that helps you solve existing problems or build new theory, which leads to new ideas.
Computer based proofs are not really readable in the same way, in many cases a particular statement being true is not really of interest, but the idea behind the proof is important. Many interesting applications and new theoretical developments lie behind these ideas, rather than some particular fact being true or false. The main benefit you can get from software is correctness, and the fact that maybe the computer can answer a question you can't, although the computer's answer may be completely noninteresting.
More importantly, formalizing modern mathematics to the point where a computer system can even work on it is an ongoing process that will take many many years. AI can't speed this up, but can probably make coming up with the proofs easier once it's done.
> Many interesting applications and new theoretical developments lie behind these ideas, rather than some particular fact being true or false. The main benefit you can get from software is correctness
That's a common attitude among mathematicians and I think it's mistaken. I think the better way to understand it is that computer proofs don't just require, but also *allow*, different kinds of abstractions.
The things that mathematicians consider to be interesting or important might change with computer proofs, but that's not necessarily a bad thing.
I mean, I'm not asking for anyone's trust really. Obviously individual mathematicians should do whatever they think is best for their careers. But my prediction is that "what is best for their careers" will ultimately turn out to be "fully embracing computers in their work". I'll either be right about that or wrong.
my dad worked in a similar/parallel field to Chomsky in academia. he had very little good to say about him, and plenty that was quite negative (about even specifically his tenure as a leading figure in linguistics, I mean) when I've asked, he described Chomsky as someone who was an intellectual bully who was abnormally/unhealthily overconfident in his own theories to the point that it fostered an unhealthy lack of debate and disagreement in the field. that i.e. if you wanted to work outside of the chomskian paradigm, you basically had to go do your research in europe where his influence wasn't as strong. if I asked about what was wrong with him in any more specificity, he would get into stuff that I cannot properly convey as am I not in linguistics myself, but I remember it being along the lines of Chomsky being overly insistent on/focused on 'elegance' in theories of linguistics and not accepting of any ideas that were more fuzzy (and therefore in my dad's assertion, realistic, practical, etc)
I don't know enough about linguistics to be able to criticize him on that topic, but based on his commentary on pretty much anything else that I do know something about, it wouldn't surprise me at all if Chomsky's opinion of his own linguistics theories was very overconfident.
Chomsky has a lot in common with the rationalists, really. He has achieved success by virtue of brazen, bullying overconfidence and a fawning audience that, for some reason, desperately wants to believe him.
He's sort of what I'd expect a well-educated Eliezer Yudkowsky to look like.
I really know shit-all about Chomsky, but boy does this map well to my vague sense of him from various snippets that one does encounter. It seems like a specifically aggressive contrarianism, where an ideas worth is intrinsically related to everyone else being wrong. Or something like that.
I’m a data scientist and it’s honestly pretty entertaining and cathartic for me to read someone like Chomsky talk about “real” science. I often do feel like I’m doing fake science and in a weird way this makes me feel seen.
I agree that he probably can’t go any deeper into the math of large language models than he already has, and it would be more satisfying to read this kind of criticism from someone who was more qualified to make it.
I'm on the side of the techbros on this one. Not for any good reason, but because im very very petty.
A long time ago I was following a linguistics course on AI. And the very first lesson the guy comes in late (which is fine, happens, we had to walk from one end of the campus to another, so him being late wasn't that much of an issue). He then says he hates latecomers, so we should always be on time, but this rule doesn't apply to him because he is the professor. Which was eyeroll worthy.
After that he, against a class filled with 90% STEM nerds who elected to follow his course, he goes on some rant on how they, the smart linguists are better at AI because while the STEM people start to smash code together, they the smart linguists first sit down and think about what actually is intelligence. Which was a really weird remark to make, as while some inter discipline rivalry between students was not uncommon, I had never encountered a prof which made such dismissive remarks of a related field.
This sadly primed us all to not follow his course that well, and mock his relevant questions about intelligence, like 'if a parrot repeats everything it says, is it intelligent?', which still baffles AI researchers today ;). Really strange difference from the 'we are more equals figuring stuff out together' tone which was more prevalent among various STEM courses.
But yeah, after 25 years I get some validation in seeing the AI bros hammering code together being right, and this dismissive linguist being wrong.
So suck it linguistics people!
But hey, at least I got a copy of Artificial Intelligence: A Modern Approach out of the deal.
No, don’t you understand the US forced Russia to go to war with Ukraine! And the Uyghur genocide shouldn’t be talked about because Israel is worse and also the Khmer Rouge is just western media exaggerating to paint a communist regime in a negative light until it isn’t and then it was also the US’s fault.
But yeah, his bullshit foreign policy takes have been around forever, it was incredibly weird and frustrating going with manufacturing consent being this seminal work for me as an undergrad to seeing how he’s not actually trying to speak truth to power, just hot takes to one specific power.
Even for very intelligent people, once you’ve adopted a central narrative, it’s hard to consider other ones. Sadly, the specific narrative that Chomsky decided to adopt requires him to excuse *practically anything* from countries unfriendly to America.
Yep, though having a linguist as a partner I’d probably dispute Chomsky’s status as “very intelligent” but certainly he should be intelligent enough to avoid these pitfalls were it not for his problematic grand narrative.
If the internet has thought me anything it is that you become famous not by avoiding rakes, but by stepping on them. (Being male and white is prob a prereq for this).
How is that “obvious”? Like I would agree that the fact that he met with Epstein doesn’t make it reasonable to assume he raped anyone, but there seems to be this assumption that Chomsky couldn’t possibly be a person who does bad things.
If all you meant by that was just “assuming he raped people because he met with Epstein and his defence of it was weird and pathetic is wrong” my bad.
He was ~82, when they met. I suppose that, of course, doesn't make it impossible, but at least very unlikely. We know that Epstein liked to engage with academics and to give money to academia. Let's put it this way: It would be far weirder for Chomsky, who has never been accused of any such crimes, to commit sex crimes at such a high age, then whatever other option you might think of. It doesn't seem reasonable to assume that every person who has ever had any dealings with Epstein is a rapist.
Yeah I agree with the last bit, I’m not sure we should take his word about everything he said about his dealings with Epstein though, he /did/ claim that Epstein had served his sentence and was thus considered to have a clean slate even though he was still on parole.
The issue I have with the “Epstein just liked to hang with academics” is it’s an excuse that’s been used to excuse Pinker and Brockman, when both of their ties to Epstein went beyond just being academics he cozied up to (Pinker argued at his first trial and Brockman famously had that email where he said that he liked all the women Epstein exposed him to).
Reading about Noam Chomsky vs AI bros and/or rationalists feels like jumping into the middle of a Godzilla vs Mothra movie. Like, I think I’m supposed to be rooting for Godzilla to win, because he’s cooler and theoretically he’s on our side this time. But I’m not totally sure.
He makes it impossible to ignore the fact that he, too, is a big, grandiose weirdo who can’t resist commenting outside of the domain of his expertise. Look at how this article begins:
I know people hold him in high regard but that’s a ludicrous statement.
I think the linguistics people feel defensive about the LLM situation. Over the past 10 years or so the AI bros have been achieving mind-blowing empirical results that the linguists not only never stood a chance of achieving, but which the majority of them still don’t understand at all.
I understand the criticism that the AI bros are just hitting a pile of data with a giant math hammer and that this approach feels lacking, but I think that criticism would be a lot more valid coming from someone who actually understands how the giant math hammer works.
The only people who dismiss the the math so blithely are the people who don’t get it, and I am certain that Noam Chomsky has no idea at all how any of this stuff works. That’s why he talks at great length about linguistics and not at all about the machine learning techniques he’s dismissing.
Can someone explain to me what an “impossible language” is?
At least he’s actually talking about linguistics this time instead of spewing bullshit foreign policy takes.
Well, it’s not unusual
Fantastic interview
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