AI transcript
The following is a conversation with Edward Gibson, or Ted, as everybody calls him. He is a
Psycho-Linguistics Professor at MIT. He heads the MIT Language Lab that investigates why human
languages look the way they do, the relationship between cultural language and how people represent,
process, and learn language. Also, he should have a book titled “Syntax, A Cognitive Approach”
published by MIT Press coming out this fall. So, look out for that.
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I enjoyed their stuff. Maybe you will too. This episode is brought to you by Yahoo Finance,
a new sponsor. And they got a new website that you should check out. It’s a website that provides
financial management, reports, information, and news for investors. Yahoo itself has been around
forever. Yahoo Finance has been around forever. I don’t know how long, but it must be over 20 years.
It survived so much. It evolved rapidly and quickly, adjusting, evolving, improving,
all of that. The thing I use it for now is there’s a portfolio that you can add your account to.
Ever since I had zero money, I used, boy, I think it’s called TD Ameritrade. I still use
that same thing. Just getting a basic mutual fund. And I think TD Ameritrade got bought
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All I know is that Yahoo Finance can integrate that and just show me everything I need to know
about my “portfolio.” I don’t have anything interesting going on, but it is still good.
To kind of monitor it, to stay in touch. Now, a lot of people I know have a lot more
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also for the entirety of the finance information for the entirety of the world. That’s all there.
The big news, the analysis of everything that’s going on, everything like that.
And I should also mention that I would like to do more and more financial episodes. I’ve done
a couple of conversations with Ray Dalio. A lot of that is about finance, but some of that is about
sort of geopolitics and the bigger context of finance. I just recently did a conversation with
Bill Ackman very much about finance. And I did a series of conversations on cryptocurrency.
Lots and lots of brilliant people. Michael Saylor, so on. Charles Hoskins and Vitalik,
and just lots of brilliant people in that space thinking about the future of money,
future of finance. Anyway, you can keep track of all of that with Yahoo Finance
for comprehensive financial news and analysis. Go to yahoofinance.com. That’s yahoofinance.com.
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I’ve been a fan of his for a long time, long before Shopify was a sponsor. I don’t even know
if he knows that Shopify sponsors this podcast. Now, just to clarify, it really doesn’t matter.
Nobody in this world can put pressure on me to have a sponsor, not to have a sponsor,
or for a sponsor to put pressure on me what I can and can’t say. I, when I wake up in the morning,
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I’ve been very fortunate in that way in many dimensions of my life, and I also have always
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I kind of suspect I’m kind of an idiot. I start my approach to the world of ideas from that place.
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in the description. And now, dear friends, here’s Edward Gibson.
[Music]
When did you first become fascinated with human language?
As a kid in school, when we had to structure sentences in English grammar, I found that
process interesting. I found it confusing as to what it was I was told to do. I didn’t
understand what the theory was behind it, but I found it very interesting.
So when you look at grammar, you’re almost thinking about like a puzzle,
like almost like a mathematical puzzle? Yeah, I think that’s right. I didn’t know I was going to
work on this at all at that point. I was really just, I was kind of a math geek person, computer
scientist. I really liked computer science. And then I found language as a neat puzzle to work on
from an engineering perspective. Actually, as I sort of accidentally, I decided after I finished
my undergraduate degree, which was computer science and math and Canada and Queens University,
I decided to go to grad school. That’s what I always thought I would do. And I went to Cambridge,
where they had a master’s in a master’s program in computational linguistics.
And I hadn’t taken a single language class before. All I’d taken was CS, computer science,
math classes, pretty much mostly as an undergrad. And I just thought this was an interesting thing
to do for a year, because it was a single year program. And then I ended up spending my whole
life doing it. So fundamentally, your journey through life was one of a mathematician and
computer scientist. And then you kind of discovered the puzzle, the problem of language and approached
it from that angle to try to understand it from that angle, almost like a mathematician or maybe
even an engineer. As an engineer, I’d say, I mean, to be frank, I had taken an AI class,
I guess it was 83 or 85, somewhere 84 in there a long time ago. And there was a natural language
section in there. And it didn’t impress me. I thought there must be more interesting things
we can do. It didn’t seem very, it seemed just a bunch of hacks to me. It didn’t seem like a real
theory of things in any way. And so I just thought this was, this seemed like an interesting area
where there wasn’t enough good work. Did you ever come across like the philosophy angle of logic?
So if you think about the 80s with AI, the expert systems, where you try to kind of
maybe sidestep the poetry of language and some of the syntax and the grammar and all that kind
of stuff and go to the underlying meaning that language is trying to communicate and try to
somehow compress that in a computer-representable way. Do you ever come across that in your studies?
I mean, I probably did, but I wasn’t as interested in it. I was trying to do the
easier problems first, the ones I could thought maybe were handleable, which is seems like the
syntax is easier, which is just the forms as opposed to the meaning. When you’re starting
talking about the meaning, that’s a very hard problem. And it still is a really, really hard
problem. But the forms is easier. And so I thought at least figuring out the forms of human language,
which sounds really hard, but is actually maybe more tractable.
So it’s interesting. You think there is a big divide, there’s a gap, there’s a distance between
form and meaning. Because that’s a question you have discussed a lot with LMS, because they’re
damn good at form. Yeah, I think it’s what they’re good at, is form. Exactly. And that’s why they’re
good, because they can do form, meanings are. Do you think there’s, oh, wow. I mean, it’s an
open question, right? How close form and meaning are. We’ll discuss it. But to me, studying form,
maybe it’s a romantic notion, gives you form is like the shadow of the bigger meaning thing
underlying language. Language is how we communicate ideas. We communicate with each other using
language. So in understanding the structure of that communication, I think you start to understand
the structure of thought and the structure of meaning behind those thoughts and communication.
To me. But to you, big gap. Yeah. What do you find most beautiful about human language?
Maybe the form of human language, the expression of human language.
What I find beautiful about human language is some of the generalizations that happen
across the human language, just within and across a language. So let me give you an example of
something which I find kind of remarkable, that is if like a language, if it has a word order
such that the verbs tend to come before their objects. And so that’s like English does that.
So we have the first, the subject comes first in a simple sentence. So I say, you know, the
dog chased the cat or Mary kicked the ball. So the subjects first, and then after the subject,
there’s the verb. And then we have objects. All these things come after in English. So it’s
generally a verb. And most of the stuff that we want to say comes after the subject. It’s the
objects. There’s a lot of things we want to say they come after. And there’s a lot of languages
like that. About 40% of the languages of the world look like that. They’re subject verb object
languages. And then these languages tend to have prepositions, these little markers on the nouns
that connect nouns to other nouns or nouns to verbs. So when I say a preposition like in or on
or of or about, I say I talk about something. The something is the object of that preposition that
we have these little markers come also just like verbs, they come before their nouns. Okay. And then
so now we look at other languages that like Japanese or or Hindi or some these are these are
so called verb final languages. Those is about maybe a little more than 40%. Maybe 45% of the
world’s languages are more I mean 50% of the world’s languages are verb final. Those tend to be
post positions, those markers, the same we have the states have the same kinds of markers
as we do in English, but they put them after. So sorry, they put them first, the markers come
first. So you say instead of, you know, talk about a book, you say a book about the opposite
order there in Japanese or in Hindi, you do the opposite and the and the talk comes at the end.
So the verb will come at the end as well. So instead of Mary kicked the ball, it’s Mary ball
kicked. And then if it’s Mary kicked the ball to John, it’s John to the to the marker there,
the preposition, it’s a post position in these languages. And so the interesting thing fascinating
thing to me is that within a language, this order aligns, it’s harmonic. And so if it’s one or the
other, it’s either verb initial or verb final, but then you then you’ll have prepositions,
prepositions or post positions. And so that and that’s across the languages that we we can look at,
we’ve got around 1000 languages for there’s around 7000 languages around on the on the earth right
now. But we have information about say word order on around 1000 of those pretty decent amount of
information. And for those 1000, which we know about, about 95% fit that pattern. So they will
have either verb and it’s about it’s about half and half or half of verb initial, like English and
half of verb final, like, like Japanese suggest to clarify verb initial is subject verb object.
That’s correct. Verb final is still subject, object verb. That’s correct. Yeah, the subject
is generally first. That’s so fascinating. I ate an apple or I apple eight. Yes. Okay. And it’s
fascinating that there’s a pretty even division in the world amongst those 4045%. Yeah, it’s
pretty, it’s pretty even. And those two are the most common by far. Those two orders, the subject
tends to be first. There’s so many interesting things. But these things are what thing I find
so fascinating is there are these generalizations within and across a language. And not only those
are the and there’s actually a simple explanation, I think, for a lot of that. And that is,
you’re trying to like, minimize dependencies between words. That’s basically the story,
I think behind a lot of why word order looks the way it is, is you were always connecting.
What is it? What is the thing I’m telling you? I’m talking to you in sentences, you’re talking
to me in sentences. These are sequences of words, which are connected. And the connections are
dependencies between the words. And it turns out that what we’re trying to do in a language is
actually minimize those dependency links. It’s easier for me to say things if the words that are
connecting for their meaning are close together. It’s easier for you in understanding if that’s
also true. If they’re far away, it’s hard to produce that and it’s hard for you to understand.
And the languages of the world within a language and across languages fit that generalization,
which is, so it turns out that having verbs initial and then having prepositions ends up
making dependencies shorter. And having verbs final and having post positions ends up making
dependencies shorter than if you cross them. If you cross them, it ends up, you just end up,
it’s possible, you can do it. You mean within a language? Within a language, you can do it.
It just ends up with longer dependencies than if you didn’t. And so languages tend to go that way.
They tend to, they call it harmonic. So it was observed a long time ago without the explanation
by a guy called Joseph Greenberg, who’s a famous typologist from Stanford. He observed a lot of
generalizations about how word order works. And these are some of the harmonic generalizations
that he observed. Harmonic generalizations about word order. There’s so many things I want to ask
you. Let me just, sometimes basics, you mentioned dependencies a few times. What do you mean by
dependencies? Well, what I mean is, in language, there’s kind of three structures to, three components
to the structure of language. One is the sounds. So cat is k-a-t-t in English. I’m not talking
about that part. I’m talking, then there’s two meaning parts. And those are the words. And
you were talking about meaning earlier. So words have a form and they have a meaning associated
with them. And so cat is a full form in English, and it has a meaning associated with whatever a cat
is. And then the combinations of words, that’s what I’ll call grammar or syntax. And that’s like
when I have a combination like the cat or two cats, okay? So where I take two different words
there and put them together, and I get a compositional meaning from putting those two different words
together. And so that’s the syntax. And in any sentence or utterance, whatever I’m talking to
you, you’re talking to me, we have a bunch of words and we’re putting them together in a sequence.
It turns out they are connected so that every word is connected to just one other word
in that sentence. And so you end up with what’s called technically a tree. It’s a tree structure.
So there’s a root of that utterance of that sentence. And then there’s a bunch of
dependence, like branches from that root that go down to the words. The words are the leaves in
this metaphor for a tree. So a tree is also sort of a mathematical construct. Yeah, it’s a graph
theoretical thing. Exactly. Yeah. So it’s fascinating that you can break down a sentence into a tree
and then when every word is hanging on to another, it’s depending on it. That’s right. And everyone
agrees on that. So all linguists will agree with that. No one is not controversial. That is not
controversial. There’s nobody sitting here. I do nothing mad at you. I don’t think so.
Okay. There’s no linguists sitting there mad at this. No, I think in every language,
I think everyone agrees that all sentences are trees at some level. Can I pause on that? Sure.
Because it’s to me, just as a layman, it’s surprising that you can break down sentences
in mostly all languages into a tree. I think so. I’ve never heard of anyone disagreeing with that.
That’s weird. The details of the trees are what people disagree about.
Well, okay. So what’s the root of a tree? How do you construct? How hard is it? What is the
process of constructing a tree from a sentence? Well, this is where, depending on what your
there’s different theoretical notions, I’m going to say the simplest thing, dependency grammar.
It’s like a bunch of people invented this. Tinier was the first French guy back in,
I mean, the paper was published in 1959, but he was working on the 30s and stuff.
So, and it goes back to, you know, philologist Pinini was doing this in ancient India. Okay.
And so, you know, doing something like this, the simplest thing we can think of is that there’s
just connections between the words to make the utterance. And so let’s just say I have like two
dogs entered a room. Okay. Here’s a sentence. And so we’re connecting two and dogs together.
That’s like, there’s some dependency between those words to make some bigger meaning.
And then we’re connecting dogs now to entered, right? And we connect a room somehow to entered.
And so I’m going to connect to room and then room back to entered. That’s the tree is I,
the root is entered. That’s the thing is like an entering event. That’s what we’re saying here.
And the subject, which is whatever that dog is, is two dogs, it was. And the connection goes back
to dogs, which goes back to them, then that goes back to two. I’m just, that’s my tree.
It starts at entered, goes to dogs down to two. And then the other side, after the verb,
the object, it goes to room. And then that goes back to the determiner or article,
whatever you want to call that word. So there’s a bunch of categories of words here we’re
noticing. So there are verbs. Those are these things that typically mark,
they refer to events and states in the world. And they’re nouns, which typically refer to
people, places and things is what people say, but they can refer to other more,
they can refer to events themselves as well. They’re marked by, you know, how they, how they,
you, the category, the part of speech of a word is how it gets used in language.
It’s like, that’s how you decide what the, what the category of a word is, not, not by the meaning,
but how it’s, how it gets used. How it’s used. What’s usually the root? Is it going to be the
verb that defies the event? Usually. Yes. Yes. Okay. Yeah. I mean, if I don’t say a verb,
then there won’t be a verb until it’ll be something else. What if you’re messing,
are we talking about language that’s like correct language? What if you’re doing
poetry and messing with stuff? Is it then, then rules got the window, right? Then it’s, no,
you’re still, no, no, no, no, no. You’re constrained by whatever language you’re dealing
with. Probably you have other constraints in poetry, such that you’re like usually in poetry,
there’s multiple constraints that you want to, like you want to usually convey multiple
meanings is the idea. And maybe you have like a rhythm or a rhyming structure as well. And
depending on, so, but you usually are constrained by your, the rules of your language for the most
part. And so you don’t violate those too much. You can violate them somewhat, but not too much.
So it has to be recognizable as your language. Like in English, I can’t say dogs to entered
room. I mean, I meant that, you know, two dogs entered a room and I can’t
mess with the order of the, the articles, the articles and the nouns. You just can’t do that.
In some languages, you can, you can mess around with the order of words much more. I mean, you
speak Russian. Russian has a much freer word order than English. And so in fact, you can move
around words in, you know, I told you that English has the subject verb object word order. So does
Russian, but Russian is much freer than English. And so you can actually mess around with the
word order. So probably Russian poetry is going to be quite different from English poetry because
the word order is much less constrained. Yeah, there’s a much more extensive culture of poetry
throughout the history of the last 100 years in Russia. And I always wondered why that is,
but it seems that there’s more flexibility in the way the language is used. There’s more,
you’re more female language easier by altering the words, altering the order of the words,
messing with it. Well, you can just mess with different things in each language. And so in
Russian, you have case markers, right? On the end, which is these endings on the nouns,
which tell you how it connects each noun connects to the verb, right? We don’t have that in English.
And so when I say, Mary kissed John, I don’t know who the agent or the patient is,
except by the order of the words, right? In Russian, you actually have a marker on the
end. If you’re using a Russian name and each of those names, you’ll also say, is it, you know,
agent, it’ll be the, you know, nominative, which is marking the subject or an accusative will mark
the object. And you could put them in the reverse order, you could put accusative first as you could
put subject, you could put the patient first, and then the verb, and then the, the, the subject,
and that would be a perfectly good Russian sentence. And it would still mean, Mary, I could
say John kissed Mary meaning Mary kissed John, as long as I use the case markers in the right way,
you can’t do that in English. And so I love the terminology of agent and patient and
and the other ones you use. Those are sort of linguistic terms, correct? Those are, those are
for like kind of meaning. Those are meaning and in subject and object are generally used for
position. So subject is just like the thing that comes before the verb and the object is
when it comes after the verb. The agent is kind of like the thing doing it. That’s kind of what
that means, right? The subject is often the person doing the action, right? The thing. So yeah.
Okay. This is fascinating. So how hard is it to form a tree in general? Is there,
is there a procedure to it? Like if you look at different languages, is it supposed to be a very
natural, like is it automatable or is there some human genius involved in? Because I think it’s
pretty automatable at this point. People can figure out the words are they figure out the morphemes,
which are the technically morphemes are the, the minimal meaning units within a language. Okay.
And so when you say eats or drinks, it actually has two morphemes in an English. There’s the,
there’s the root, which is the verb. And then there’s some ending on it, which tells you,
you know, that’s this third person, third person singular, say what morphemes are morphemes are
just the minimal meaning units within a language. And then a word is just kind of the things we
put spaces between in English and 10, they have a little bit more, they have the morphology as well.
They have the endings, this inflectional morphology on the endings on the roots.
They modify something about the word that adds additional meaning.
They tell you, yeah, yeah. And so we have a little bit of that in English, very little,
you have much more in Russian, for instance. And, and, but we have a little bit in English.
And so we have a little on the, on the nouns, you can say it’s either singular or plural.
And, and you can say, same thing for, for, for verbs, like simple past tense, for example,
it’s like, you know, notice in English, we say drinks, you know, he drinks, but everyone else
says, I drink, you drink, we drink, it’s unmarked in a way. And then, but in the past tense, it’s
just drank there for everyone. There’s no morphology at all for past tense. There is morphology,
it’s marking past tense, but it’s kind of, it’s an irregular now. So we don’t even, you know,
it drink to drink, you know, it’s not even a regular word. So in most verbs, many verbs,
there’s an ED, we kind of add, so walk to walked, we add that to say it’s the past tense,
that I just happened to choose an irregular because the high frequency word and the high
frequency words tend to have irregular as an English for.
What’s an irregular? Irregular is just, there’s, there isn’t a rule. So drink to drink is an,
it’s an irregular. Drink, drink, okay, as opposed to walk, walked, talked, talked.
And there’s a lot of irregular, irregular as in English. There’s a lot of irregular as in
English. The, the, the frequent ones, the common words tend to be irregular. There’s many, many
more low frequency words and those tend to be, those are regular ones.
The evolution of the irregular is fascinating because it’s essentially slang that’s sticky
because you’re breaking the rules and then everybody uses it and doesn’t follow the rules.
And they, they say screw it to the rules. It’s fascinating. So you said it, morphemes,
lots of questions. So morphology is what, the study of morphemes?
Morphology is the, is the connections between the morphemes onto the roots, the roots. So in
English, we mostly have suffixes. We have endings on the words, not very much, but a little bit.
And as opposed to prefixes, some words, depending on your language, can have,
you know, mostly prefixes, mostly suffixes or mostly, or both. And then even languages,
several languages have things called infixes where you have some kind of a general
form for the, for the root and you put stuff in the middle. You change the vowels.
That’s fascinating. That’s fascinating. So in general, there’s what, two morphemes per word,
usually one or two or three? Well, in English, it’s one or two. In English,
it tends to be one or two. There can be more. You know, in other languages, you know, language,
language like, like Finnish, which has a very elaborate morphology, there may be
10 morphemes on the end of a root. Okay. And so there may be millions of forms of a given word.
Okay. Okay. I will ask the same question over and over. But
how does the, just sometimes to understand things like morphemes, it’s nice to just ask
the question, how does these kinds of things evolve? So you have a great book studying sort of the,
how, how the cognitive processing, how language used for communication,
so the mathematical notion of how effective a language is for communication, what role that
plays in the evolution of language. But just high level, like how do we, how does a language evolve
with where English has two morphemes or one or two morphemes per word and then Finnish has
infinity per word? So what, how does that, how does that happen? Is it just people?
That’s a really good question. Yeah. That’s a very good question is like,
why do languages have more morphology versus less morphology? And I don’t think we know the
answer to this. I don’t, I think there’s just like a lot of good solutions to the problem of
communication. And so like, I believe, as you hinted that language is an invented system by humans
for communicating their ideas. And I think we, it comes down to, we label the things we want to
talk about. Those are the morphemes and words. Those are the things we want to talk about in the
world and we invent those things. And then we put them together in ways that are easy for us
to convey, to process. But that’s like a naive view. And I don’t, I mean, I, I think it’s probably
right, right? It’s naive and probably right. I don’t know if it’s naive. I think it’s simple.
Simple. Yeah. I think naive is, naive is an indication that it’s an incorrect somehow,
it’s a trivial to too simple. I think it could very well be correct. But it’s interesting how
sticky it feels like two people got together. It’s just, it just feels like once you figure out
certain aspects of a language that just becomes sticky and the tribe forms around that language,
maybe the language, maybe the tribe forms first and then the language evolves. And then you just
kind of agree and you stick to whatever that is. I mean, these are very interesting questions. We
don’t know really about how words, even words get invented very much about, you know, we don’t
really, I mean, assuming they get invented, they, we don’t really know how that process
works and how these things evolve. What we have is kind of a current picture, a current picture of
a few thousand languages, a few thousand instances. We don’t have any pictures of really how these
things are evolving really. And then the evolution is massively, you know, confused by contact,
right? So as soon as one language group, one group runs into another, we are smart, humans are
smart, and they take on whatever is useful in the other group. And so any kind of contrast,
which you’re talking about, which I find useful, I’m going to, I’m going to start using as well.
So I worked a little bit in specific areas of words in number words and in color words and in
color words. So we have in English, we have around 11 words that everyone knows for colors.
And many more, if you happen to be interested in color for some reason or other, if you’re a
fashion designer or an artist or something, you may have many, many more words. But we can see
millions. Like if you have normal color vision, normal trichrometric color vision, you can see
millions of distinctions in color. So we don’t have millions of words. You know, the most efficient,
no, the most detailed color vocabulary would have over a million terms to distinguish all
the different colors that we can see. But of course, we don’t have that. So it’s somehow,
it’s been, it’s kind of useful for English to have evolved in some way to, there’s 11 terms
that people find useful to talk about, you know, black, white, red, blue, green, yellow, purple,
gray, pink, and I probably missed something there. Anyway, there’s 11 that everyone knows.
But you go to different cultures, especially the non-industrialized cultures, and there’ll be
many fewer. So some cultures will have only two, believe it or not, that the Danai in Papua New Guinea
have only two labels that the group uses for color. And those are roughly black and white.
They are very, very dark and very, very light, which are roughly black and white. And you might
think, oh, they’re dividing the whole color space into, you know, light and dark or something.
That’s not really true. They mostly just only label the light, the black and the white things.
They just don’t talk about the colors for the other ones. And so, and then there’s other groups,
I’ve worked with a group called the Chimani down in, in Bolivia, in South America, and they have
three words that everyone knows, but there’s a few others that are, that, that several people,
that many people know. And so they have me, it’s kind of depending on how you count between
three and seven words that the group knows. Okay. And again, they’re black and white,
everyone knows those. And red, red is, you know, like that tends to be the third word that everyone,
that cultures bring in. If there’s a word, it’s always red, the third one. And then after that,
it’s kind of all bets are off about what they bring in. And so after that, they bring in a sort
of a big blue, green group, group, they have one for that. And then they have, and then,
you know, different people have different words that they’ll use for other parts of the space.
And so anyway, it’s probably related to what they want to talk, what they, not what they,
not what they see, because they see the same colors as we see. So it’s not like they have,
they don’t, they have a weak, a low color palette and the things they’re looking at. They’re looking
at a lot of beautiful scenery. Okay. A lot of different colored flowers and berries and things.
And, you know, and so there’s lots of things of very bright colors, but they just don’t label
the color in those cases. And the reason probably we don’t know this, but we think probably what’s
going on here is that what you do, why you label something is you need to talk to someone else
about it. And why do I need to talk about a color? Well, if I have two things which are identical
and I want you to give me the one that’s different and in the only way it varies is color,
then I invent a word which tells you, you know, this is the one I want. So I want the red sweater
off the rack, not the, not the green sweater, right? There’s two. And so those, those things will
be identical, because these are things we made and they’re dyed and there’s nothing different
about them. And so in, in industrialized society, we have, you know, everything, everything we’ve
got is pretty much arbitrarily colored. But if you go to a non-industrialized group, that’s not
true. And so they don’t, suddenly they’re not interested in color. If you bring bright colored
things to them, they like them just like we like them. Bright colors are great. They’re beautiful.
They are, but they just don’t need to, no need to talk about them. They don’t have.
So probably color words is a good example of how language evolves from sort of function
when you need to communicate the use of something. I think so. Then you kind of invent different
variations. And, and basically, you can imagine that the evolution of a language has to do with
what the early tribes doing, like what, what they want it, what, what kind of problems they’re
facing them. And they’re quickly figuring out how to efficiently communicate the solution to those
problems, whether it’s aesthetic or functional, all that kind of stuff, running away from a
mammoth or whatever. But you know, it’s, so I think what you’re pointing to is that we don’t have
data on the evolution of language, because many languages have formed a long time ago,
so you don’t get the chatter. We have a little bit of like old English to modern English,
because there was a writing system, and we can see how old English looked. So the word order
changed, for instance, in old English to middle English to modern English. And so it, you know,
we can see things like that, but most languages don’t even have a writing system. So of the
7000, only, you know, a small subset of those have a writing system. And even if they have a
writing system, they, it’s not a very modern writing system. And so they don’t have it. So we
just basically have for Mandarin, for Chinese, we have a lot of, a lot of evidence from, from,
for long time and for English, and not for much else, not from in German a little bit,
but not for a whole lot of like long term language evolution. We don’t have a lot.
Well, you get snapshots is what we’ve got of current languages.
Yeah, you get an inkling of that from the rapid communication on certain platforms,
like on Reddit, there’s different communities, and they’ll come up with different slang,
usually from my perspective, German by a little bit of humor, or maybe mockery or whatever it’s,
you know, just talking shit in different kinds of ways. And you could see the evolution
of language there. Because I think a lot of things on the internet, you don’t want to be the
boring mainstream. So you like want to deviate from the proper way of talking.
And so you get a lot of deviation, like rapid deviation, then when communities collide,
you get like, just like you said, humans adapt to it. And you can see it through the
lungs of humor. I mean, it’s very difficult to study, but you can imagine like 100 years from
now, well, if there’s a new language born, for example, we’ll get really high resolution data.
I mean, English is changing. English changes all the time. All languages change all the time.
So, you know, there’s a famous result about the Queen’s English. So if you look at the Queen’s
vowels, the Queen’s English is supposed to be, you know, originally the proper way for the talk
was sort of defined by whoever the Queen talked, or the King, whoever was in charge. And so if
you look at how her vowels changed from when she first became Queen in 1952 or ’53, when she was
currently the first, I mean, that’s Queen Elizabeth, who died recently, of course, until,
you know, 50 years later, her vowels changed, her vowels shifted a lot. And so that, you know,
even in the sounds of British English, in her, the way she was talking was changing,
the vowels were changing slightly. So that’s just in the sounds there’s changed. I don’t know what’s,
you know, we’re, I’m interested. We’re all interested in what’s driving any of these
changes. The word order of English changed a lot over a thousand years, right? So it used to look
like German. You know, it used to be a verb final language with case marking, and it shifted
to a verb-medial language, a lot of contact. So a lot of contact with French. And it became
verb-medial language with no case marking. And so it became this, you know, verb, verb-initially
thing. So and so that’s evolving. It totally evolved. And so it may very well, I mean, you know,
it doesn’t evolve maybe very much in 20 years is maybe what you’re talking about. But over 50
and 100 years, things change a lot, I think. We’ll now have good data on it, which is great.
That’s for sure. Can you talk to what is syntax and what is grammar? So you wrote a book on syntax.
I did. You were asking me before about what, you know, how do I figure out what a dependency
structure is? I’d say the dependency structures aren’t that hard. Generally, I think it’s a lot
of agreement of what they are for almost any sentence in most languages. I think people will
agree on a lot of that. There are other parameters in the mix such that some people think there’s a
more complicated grammar than just a dependency structure. And so, you know, like Noam Tromsky,
he’s the most famous linguist ever. And he is famous for proposing a slightly more complicated
syntax. And so he invented phrase structure grammar. So he’s well known for many, many
things. But in the 50s, in the early 60s, like the late 50s, he was basically figuring out what’s
called formal language theory. So, and he figured out sort of a framework for figuring out how
complicated language, you know, a certain type of language might be so-called phrase structure
grammars of language might be. And so his idea was that maybe we can think about the complexity
of a language by how complicated the rules are. And the rules will look like this. They will have
a left-hand side and they’ll have a right-hand side. Something on the left-hand side will expand
to the thing on the right-hand side. So we’ll say we’ll start with an S, which is like the root,
which is a sentence. And then we’re going to expand to things like a noun phrase and a verb
phrase is what he would say, for instance. An S goes to an NP and a VP is a kind of a phrase
structure rule. And then we figure out what an NP is. An NP is a determiner and a noun, for instance.
And verb phrase is something else, is a verb and another noun phrase and another NP, for instance.
Those are the rules of a very simple phrase structure. And so he proposed phrase structure
grammar as a way to sort of cover human languages. And then he actually figured out that, well,
depending on the formalization of those grammars, you might get more complicated or less complicated
languages. So he said, well, these are things called context-free languages, that rule that he
thought human languages tend to be what he calls context-free languages. But there are simpler
languages, which are so-called regular languages, and they have a more constrained form to the rules
of the phrase structure of these particular rules. So he basically discovered and kind of invented
ways to describe the language. And those are phrase structure, a human language. And he was
mostly interested in English initially in his work in the ’50s.
So quick questions around all this. So formal language theory is the big field of just studying
language formally. Yes. And it doesn’t have to be human language there. We can have computer
languages, any kind of system which is generating some set of expressions in a language. And those
could be like the statements in a computer language, for example. So it could be that
or it could be human language. So technically, you can study programming languages?
Yes. And have been heavily studied using this formalism. There’s a big field of programming
language within the formal language. Okay. And then phrase structure, grammar, is this idea
that you can break down language into this S-N-P-V-P type of thing? It’s a particular
formalism for describing language. And Chomsky was the first one. He’s the one who figured
that stuff out back in the ’50s. And that’s equivalent, actually. The context-free grammar
is actually kind of equivalent in the sense that it generates the same sentences as a
dependency grammar would. The dependency grammar is a little simpler in some way. You just have a
root and it goes, like, we don’t have any of these, the rules are implicit, I guess,
and we just have connections between words. The phrase structure, grammar is kind of a
different way to think about the dependency grammar. It’s slightly more complicated, but
it’s kind of the same in some ways. So to clarify, dependency grammar is the framework under which
you see language and you make a case that this is a good way to describe language. And
Noam Chomsky is watching this. He’s very upset right now, so I’m just kidding. But what’s the
difference between where’s the place of disagreement between phrase structure, grammar, and dependency
grammar? They’re very close. So phrase structure, grammar, and dependency grammar aren’t that far
apart. I like dependency grammar because it’s more perspicuous, it’s more transparent about
representing the connections between the words. It’s just a little harder to see in phrase structure
grammar. The place where Chomsky sort of devolved or went off from this is he also thought there was
something called movement. And that’s where we disagree. That’s the place where I would say
we disagree. And I mean, maybe we’ll get into that later. But the idea is, if you want to,
do you want me to explain that? No, I would love to explain movement. You’re saying so many
interesting things. Okay, so here’s the movement is Chomsky basically sees English and he says,
okay, I said, you know, we had that sentence earlier, like it was like two dogs entered the
room. It’s changed a little bit, say two dogs will enter the room. And he notices that, hey,
English, if I want to make a question, a yes, no question from that same sentence, I say,
instead of two dogs will enter the room, I say, will two dogs enter the room? Okay, there’s a
different way to say the same idea. And it’s like, well, the auxiliary verb that will thing,
it’s at the front as opposed to in the middle. Okay. And so, and he looked, you know, if you
look at English, you see that that’s true for all those modal verbs. And for other kinds of
auxiliary verbs in English, you always do that. You always put an auxiliary verb at the front.
And what he’s, when he saw that, so, you know, if I say, I can win this bet, can I win this bet,
right? So I move a can to the front. So actually, that’s a theory, I just gave you a theory there.
He talks about it as movement, that word in the declarative is the root is the sort of default
way to think about the sentence. And you move the auxiliary verb to the front, that’s a movement
theory. Okay. And he just thought that was just so obvious that it must be true that there’s
nothing more to say about that, that this is how auxiliary verbs work in English. There’s a movement
rule such that you’re move, like to get from the declarative to the interrogative, you’re moving
the auxiliary to the front. And it’s a little more complicated as soon as you go to simple,
simple present and simple past, because, you know, if I say, you know, John slept, you have to say,
did John sleep, not slept John, right? And so you have to somehow get an auxiliary verb. And I
guess underlyingly, it’s like slept is it’s a little more complicated than that. But that’s his
idea. There’s a movement. Okay. And so a different way to think about that, that isn’t, I mean,
he ended up showing later. So he proposed this theory of grammar, which has movement. And there’s
other places where he thought there’s movement, not just auxiliary verbs, but things like the passive
in English and things like questions, WH questions, a bunch of places where he thought there’s also
movement going on. And each one of those, these things, there’s words, well, phrases and words
are moving around from one structure to another, which he called deep structure to surface structure.
I mean, there’s like two different structures in his theory. Okay. There’s a different way to
think about this, which is there’s no movement at all. There’s a lexical copying rule such that
the word will or the word can, these auxiliary verbs, they just have two forms. And one of them
is the declarative and one of them is the interrogative. And you basically have the declarative
one and, oh, I form the interrogative or I can form one from the other. It doesn’t matter which
direction you go. And I just have a new entry, which has the same meaning, which has a slightly
different argument structure, argument structure. It’s a fancy word for the ordering of the words.
And so if I say, you know, it was the dogs, two dogs can or will enter the room. There’s two forms
of will. One is will declarative. And then, okay, I’ve got my subject to the left. It comes before
me. And the verb comes after me in that one. And then the will interrogative is like, oh,
I go first interrogative will is first. And then I have the subject immediately after and then the
verb after that. And so you just, you can just generate from one of those words, another word
with a slightly different argument structure with different ordering. And these are just lexical
copies. They’re not necessarily moving from one to another. There’s no movement. There’s a romantic
notion that you have like one main way to use a word. And then you could move it around, which is
essentially what movement is applying. But that’s the lexical copying is similar. So then we do
lexical copying for that same idea that maybe the declarative is the source and then we can copy it.
And so an advantage for, well, there’s multiple advantages of the lexical copying story. It’s
not my story. This is like Ivan Sog, linguists, a bunch of linguists have been proposing these
stories as well, you know, in tandem with the movement story. Okay, you know, he’s,
he’s Ivan Sog died a while ago, but he was one of the proponents of the non-movement of the
lexical copying story. And so that is that a great advantage is, well, Chomsky, really famously in
1971, showed that the movement story leads to learnability problems. It leads, it leads to
problems for, for how language is learned. It’s really, really hard to figure out what the underlying
structure of a language is. If you have both phrase structure and movement, it’s like really
hard to figure out what came from what. There’s like a lot of possibilities there. If you don’t
have that problem, learning, the learning problem gets a lot easier. Just say there’s lexical copies.
And when we say the learning problem, do you mean like humans learning a new language?
Yeah, just learning English. So baby is lying around listening to the crib, listening to me
talk. And, you know, how are they learning English? Or, or, you know, maybe it’s a two-year-old who’s
learning, you know, interrogatives and stuff or one, you know, they’re, you know, how are they
doing that? Are they doing it from like, are they figuring out or like, you know, so Chomsky said,
it’s impossible to figure it out, actually. He said it’s actually impossible, not, not hard,
but impossible. And therefore, that’s what that’s where universal grammar comes from,
is that it has to be built in. And so what they’re learning is that there’s some built in movement
is built in in his story is absolutely part of your language module. And, and then you are,
you’re just setting parameters, you’re said depending on English is just sort of a variant
of the universal grammar. And you’re figuring out, oh, which orders do those English do these
things? That’s the, the non-movement story doesn’t have this. It’s like much more bottom up.
You’re learning rules. You’re learning rules one by one. And, oh, there’s this, this word is connected
to that word. A great advantage, another advantage, it’s learnable. Another advantage of it is that
it predicts that not all auxiliaries might move, like it, it might depend on the word, depending
on whether you, and that turns out to be true. So there’s words that, that don’t really work
as auxiliar, you know, they work in declarative and not in an interrogative. So I can say,
I’ll give you the opposite first. If I can say, aren’t I invited to the party? Okay. And that’s an,
that’s an interrogative form, but it’s not from I aren’t invited to the party. There is no I aren’t,
right? So that’s, that’s interrogative only. And, and then we also have forms like ought. I,
I ought to do this. And, and I guess some British, old British people can say,
exactly. It doesn’t sound right, does it? For me, it sounds ridiculous. I don’t even think
ought is great, but I mean, I totally recognize I ought to do. It is not too bad, actually. I can
say ought to do this. That sounds pretty good. Yeah. If I’m trying to sound sophisticated, maybe.
I don’t know. It just sounds completely out to me. Yeah. Anyway, it’s, it’s, so there are variants
here. And a lot of these words just work in one versus the other. And, and that’s like fine under
the lexical copying story. It’s like, well, you just learn the usage, whatever the usage is,
is what you, is what you do with this, with this word. But it doesn’t, it’s a little bit harder
in the movement story, the movement story, like that’s an advantage, I think of lexical copying
and in all these different places, there’s, there’s all these usage variants, which make the movement
story a little bit harder to work. So one of the main divisions here is the movement story versus
the lexical copy story that has to do about the auxiliary words and so on. But if you rewind to
the phrase structure grammar versus dependency grammar, those are equivalent in some sense
in that for any dependency grammar, I can generate a dependency, a phrase structure grammar, which
generates exactly the same sentences. I just, I just like the dependency grammar formalism because
it makes something really salient, which is the dependent, the lengths of dependencies between
words, which isn’t so obvious in the, in the phrase, in the phrase structure, it’s just kind
of hard to see. It’s in there. It’s just very, very, it’s opaque. Technically, I think phrase
structure grammar is mappable to dependency grammar. And vice versa. And vice versa. But there’s like
these like little labels S and PVP. Yeah. For a particular dependency grammar, you can make a
phrase structure grammar, which generates exactly those same sentences and vice versa.
But there are many phrase structure grammars, which you can’t really make a dependency grammar.
I mean, there, you can do a lot more in a phrase structure grammar, but you get many more of these
extra nodes, basically, you can have more structure in there. And some people like that. And maybe
there’s value to that. I, I don’t like it. Well, for you, so we should clarify. So dependency grammar
is just, well, one word depends on only one other word and you form these trees.
And that makes, it really puts priority on those dependencies, just like as a, as a tree that you
can then measure the distance of the dependency from one word to the other, they can then map to
the cognitive processing of the, of these sentences, how well, how easy it is to understand
all that kind of stuff. So it just puts the focus on just like the mathematical
distance of dependence between words. So like, it’s just a good different focus.
Absolutely. Just continue on a thread of Chomsky because it’s really interesting because it,
as you’re discussing disagreement to the degree there’s disagreement, you’re also telling the
history of the study of language, which is really awesome. So you mentioned context free versus regular.
Does that distinction come into play for dependency grammars?
No, not at all. I mean, regular languages are too simple for human languages. They are,
it’s a part of the hierarchy, but human languages are in the phrase structure world are definitely,
at least context free, maybe a little bit more, a little bit harder than that. But so there’s
something called context sensitive as well, where you can have, like this is just the formal language
description. In a context free grammar, you have one, this is like a bunch of like formal
language theory we’re doing here. I love it. Okay. So you have a left hand side category,
and you’re expanding to anything on the right is a, that’s a context free. So like the idea is that
that category on the left expands in independent of context to those things, whatever they’re on
the right, doesn’t matter what. And a context sensitive says, okay, I actually have more than
one thing on the left. I can tell you only in this context, you know, I have maybe you have like a
left and a right context or just a left context or a right context, I have two or more stuff on the
left tells you how to expand that those things in that way. Okay. So it’s context sensitive.
A regular language is just more constrained. And so it, it doesn’t allow anything on the right.
It allows very, it allows, basically, it’s a one very complicated rule is kind of what a regular
language is. And so it doesn’t have any, let’s just say long distance dependencies, it doesn’t
allow recursion, for instance, there’s no recursion. Yeah, recursion is where you, which is human
languages have recursion, they have embedding, and you can’t, well, it doesn’t allow center embedded
recursion, which human languages have, which is what center embedded recursion within a sentence,
within a sentence. Yeah, within a sentence. So here we’re going to get to that. But I, you know,
the formal language stuff is a little aside, Chomsky wasn’t proposing it for human languages
even, he was just pointing out that human languages are context free. And then he was most in, for,
for human, because that was kind of stuff we did for formal languages. And what he was most interested
in was human language. And that’s like the, the movement is where we, we, we, where, where he
sort of set off in, on the, I would say a very interesting, but wrong foot, it was kind of
interesting. It’s a very, I agree, it’s kind of a very interesting history. So there’s a set,
he proposed this multiple theories in 57 and then 65, they’re, they all have this framework,
though, was phrase structure plus movement, different versions of the, of the phrase structure
and the movement in the 57, these are the most famous original bits of Chomsky’s work. And then
71 is when he figured out that those lead to learning problems, that, that there’s cases where
a kid could never figure out which rule, which set of rules was intended. And, and so, and then
he said, well, that means it’s innate. It’s kind of interesting. He just really thought the movement
was just so obviously true that he couldn’t, he didn’t even entertain giving it up. It’s just
obvious that that’s obviously right. And it was later where people figured out that there’s all
these like subtle ways in which things would, which look like generalizations aren’t generalizations,
and they, you know, across the category, they’re, they’re word specific and they have, and they,
they kind of work, but they don’t work across various other words in the category. And so it’s
easier to just think of these things as lexical copies. And I think he was very obsessed. I don’t
know, I’m guessing that he just, he really wanted this story to be simple in some sense and language
is a little more complicated. In some sense, you know, he didn’t like words. He never talks about
words. He likes to talk about combinations of words and words are, you know, look up a dictionary,
there’s 50 senses for a common word, right? The word take will have 30 or 40 senses in it.
So there’ll be many different senses for common words. And he just doesn’t think about that. It’s,
or doesn’t think that’s language. I think he doesn’t think that’s language. He thinks that
words are distinct from combinations of words. I think they’re the same. If you look at my brain
in the scanner, while I’m listening to a language I understand, and you compare, I can localize my
language network in a few minutes in like 15 minutes. And what you do is I listen to a language I
know, I listen to, you know, maybe some language I don’t know, or I listen to muffled speech, or I
read sentences, and I read non-words, like I do anything like this, anything that sort of really
like English and anything that’s not very like English. So I’ve got something like it and not,
and I got a control. And the voxels, which is just, you know, the 3D pixels in my brain that are
responding most is a language area. And that’s this left lateralized area in my head. And,
and wherever I look in that network, if you look for the combinations versus the words,
it’s, it’s, it’s everywhere. It’s the same. That’s fascinating. And so it’s like hard to find,
there are no areas that we know. I mean, that’s, it’s a little overstated right now. At this,
at this point, the technology isn’t great. It’s not bad, but we have the best, the best way to
figure out what’s going on in my brain when I’m listening or reading language is to use
FMRI, functional magnetic resonance imaging. And that’s a very good localization method. So I can
figure out where exactly these signals are coming from pretty, you know, down to, you know, millimeters,
you know, cubic millimeters are smaller, okay, very small, we can figure those out very well.
The problem is the when, okay, it’s, it’s measuring oxygen, okay, and oxygen takes
a little while to get to those cells. So it takes on the order of seconds. So I talk fast. I probably
listen fast and like, and probably understand things really fast. So a lot of stuff happens
in two seconds. And so to say that we know what’s going on, that the words right now in that network,
our best guess is that whole network is doing something similar, but maybe different parts
of that network are doing different things. And that’s probably the case. We just don’t have very
good methods to figure that out right at this moment. And so since we’re kind of talking about the
history of the study of language, what other interesting disagreements, and you’re both at
MIT, or were for a long time, what kind of interesting disagreements, their attention of
ideas are there between you and Noam Chomsky. And we should say that Noam was in the linguistics
department. And you’re, I guess, for a time were affiliated there, but primarily brain and cognitive
science department, which is another way of studying language. And you’ve been talking about
FMRI. So like, what, is there something else interesting to bring to the surface about the
disagreement between the two of you, or other people in the industry? Yeah, I mean, I’ve been at
MIT for 31 years since 1993, and Chomsky’s been there much longer. So I met him, I knew him,
I met when I first got there, I guess, and I, and we would interact every now and then. I’d say that,
so I tell you, our biggest difference is our methods. And so that’s the biggest difference
between me and Noam, is that I gather data from people. I do experiments with people and I gather
corpus data, whatever, whatever corpus data is available, and we do quantitative methods to
evaluate any kind of hypothesis we have. He just doesn’t do that. And so, you know, he has never
once been associated with any experiment or corpus work ever. And so it’s all thought experiments.
It’s his own intuitions. So I just don’t think that’s the way to do things. That’s a, that’s a,
you know, across the street, they’re across the street from us, kind of difference between
brain and cog sci and linguistics. I mean, not all linguists, some of the linguists,
depending on what you do, more speech oriented, they do more quantitative stuff. But in the,
in the meaning words and, well, it’s combinations of words and text semantics,
they tend not to do experiments and corpus analyses. So in linguistics size, probably,
but the method is a symptom of a bigger approach, which is sort of a psychology philosophy side on
Noam. And for you, it’s more sort of data driven, sort of almost like mathematical approach.
Yeah, I mean, I’m a psychologist. So I would say we’re in psychology. You know, I mean,
brain and cognitive sciences is MIT’s old psychology department. It was a psychology
department up until 1985. And that became the brain and cognitive science department.
And so I, I mean, my training isn’t, I call, I mean, my training is math and computer science,
but I’m a psychologist. I mean, I mean, I don’t know what I am.
So data driven psychologist. Yeah, you are. I am what I am. But I’m having to be called a linguist.
I’m happy to be called a computer scientist. I’m happy to be called a psychologist, any of those
things. But in the actual, like how that manifests itself outside of the methodology is like these
differences, these cell differences about the movement story versus the lexical copy story.
Yeah, those are theories, right? So the theories, like the theories are, but I think that the reason
we differ in part is because of how we evaluate the theories. And so I evaluate theories quantitatively
and Noam doesn’t. Got it. Okay, well, let’s, let’s explore the theories that you explore in your
book. Let’s return to this dependency grammar framework of looking at language. What’s a good
justification why the dependency grammar framework is a good way to explain language? What’s your
intuition? So the reason I like dependency grammar, as I’ve said before, is that it’s very
transparent about its representation of distance between words. So it’s like, it all it is, is
you’ve got a bunch of words you’re connecting together to make a sentence. And a really neat
insight, which turns out to be true, is that the further apart the pair of words are that you’re
connecting the harder it is to do the production, the harder it is to do the comprehension is as
harder to produce, hard to understand when the words are far apart, when they’re close together,
it’s easy to produce and it’s easy to comprehend. Let me give you an example. Okay, so we have,
in any language, we have mostly local connections between words, but they’re abstract, the
connections are abstract, they’re between categories of words. And so you can always
make things further apart. If you put your, if you add modification, for example, after a noun,
so a noun in English comes before verb, the subject noun comes before verb. And then there’s an
object after, for example, so I can say what I said before, you know, the dog entered the room or
something like that. So I can modify dog. If I say something more about dog after it, then what I’m
doing is, indirectly, I’m lengthening the dependence between dog and entered by adding more stuff to
it. So I just make it explicit here if I say the boy who the cat scratched cried. We’re going to
have a mean cat here. And so what I’ve got here is I get the boy cried, it would be a very short,
simple sentence. And I just told you something about the boy. And I told you it was the boy
who the cat scratched. Okay. So the cry is connected to the boy. The cry at the end is
connected to the boy in the beginning. Right. And so I can do that. And I can say that that’s a
perfectly fine English sentence. And I can say the cat, which the dog chased ran away or something.
Okay, I can do that. But it’s really hard. And so I, but it’s really hard now. I’ve got, you know,
whatever I have here, I have the boy who the cat. Now let’s say I try to modify cat. Okay. The boy
who the cat, which the dog chased scratched ran away. Oh my God, that’s hard, right? I can,
I’m sort of just working that through in my head how to produce and how to, and it’s really very,
just horrendous to understand. It’s not so bad. At least I’ve got intonation there to sort of mark
the boundaries and stuff. But it’s, that’s really complicated. That’s sort of English in a way. I
mean, that follows the rules of English. But so what’s interesting about that is, is that what
I’m doing is nesting dependencies there. I’m putting one, I’ve got a subject connected to a verb
there. And then I’m modifying that with a clause, another clause, which happens to have a subject
and a verb relation. I’m trying to do that again on the second one. And what that does is it lengthens
out the dependence, multiple dependents actually get lengthened out there. The dependencies get
longer, on the outside ones get long, and even the ones in between get kind of long. And you just,
so what’s fascinating is that that’s bad. That’s really horrendous in English. But that’s horrendous
in any language. And so in no matter what language you look at, if you do, just figure out some
structure where I’m going to have some modification following some head, which is connected to
some later head, and I do it again, it won’t be good. It guaranteed. Like 100%, that will be
uninterpretable in that language, in the same way that was uninterpretable in English.
Just clarify, the distance of the dependencies is whenever the boy cried, there’s a dependence
between two words, and then you counting the number of what morphemes between them.
That’s a good question. I just say words. Your words are morphemes between. We don’t know that.
Actually, that’s a very good question. What is the distance metric? But let’s just say it’s words.
Sure. Okay. And you’re saying the longer the distance to that dependence, the more, no matter
the language, except legalese. Even legalese. We’ll talk about it. Okay. But that the people
will be very upset that speak that language, not upset, but they’ll either not understand it,
or they’ll be like, their brain will be working in overtime. Yeah. They will have a hard time
either producing or comprehending it. They might tell you that’s not their language.
It’s sort of the language. They’ll agree with each of those pieces as part of the language,
but somehow that combination will be very, very difficult to produce and understand.
Is that a chicken or the egg issue here? Well, I’m giving you an explanation.
I’m giving you two kinds of explanations. I’m telling you that center embedding,
that’s nesting, those are synonyms for the same concept here. And the explanation for what,
those are always hard. Center embedding and nesting are always hard. And I give you an
explanation for why they might be hard, which is long distance connections. There’s a,
when you do center embedding, when you do nesting, you always have long distance connections
between the dependents. You just, and so that’s not necessarily the right explanation. It just
happens. I can go through reasons why that’s probably a good explanation. And it’s not really
just about one of them. So probably it’s a pair of them or something of these dependents that you
get long, that drives you to be really confused in that case. And so what the behavioral
consequence there, I mean, we, this is kind of methods, like how do we get at this? You could
try to do experiments to get people to produce these things. They’re going to have a hard time
producing them. You can try to do experiments to get them to understand them and see how well
they understand them, can they understand them. Another method you can do is give people partial
materials and ask them to complete them, you know, those, those center embedded materials,
and they, they’ll fail. So I’ve done that. I’ve done all these kinds of things.
So, wait a minute. So central embedding, meaning like you take a normal sentence,
like boy cried and inject a bunch of crap in the middle. Yes. That separates the boy and the
cried. Yes. Okay. That’s central bedding. And nesting is on top of that. No, no, nesting is the
same thing. Center embedding, those are totally equivalent terms. I’m sorry, I sometimes use
one in some terms. Oh, got it, got it. They don’t need anything different. Got it. And then
what you’re saying is there’s a bunch of different kinds of experiments you can do. I mean, I like
to understanding one is like, have more embedding, more central bedding, is it easier or harder to
understand, but then you have to measure the level of understanding, I guess. Yeah. Yeah, you could.
I mean, there’s multiple ways to do that. I mean, there’s, there’s the simplest ways just to ask
people how good is it sound, how natural is the sound. That’s a very blunt, but very good measure.
It’s very, very reliable. People will do the same thing. And so it’s like, I don’t know what it means
exactly, but it’s doing something such that we’re measuring something about the confusion,
the difficulty associated with those. And those, like, those are giving you a signal,
that’s why you can say them. Yeah. Okay. What about the completion of the central bed?
So if you give them a partial sentence, say I say the book which the author who, and I ask you to
now finish that off for me. I mean, either say it, but you can just say it’s written in front
of you and you can just type and have as much time as you want. They will, even though that one’s
not too hard, right? So if I say it’s like the book, it’s like, oh, the book which the author who I
met wrote was good. You know, that’s a very simple completion for that. You know, if I give that
completion online somewhere to a, you know, a crowdsourcing platform and ask people to complete
that, they will miss off of a verb very regularly, like half of the time, maybe two thirds of the
time, they’ll say, they’ll just leave off one of those verb phrases. Even with that simple, so I’ll
say the book which the author who, and they’ll say was, they won’t have, that you need three verbs,
right? I need three verbs are who I met wrote was good, and they’ll give me two. They’ll say,
who was famous was good or something like that. They’ll just give me two. And that’ll happen about
60% of the time. So 40%, maybe 30, they’ll do it correctly, correctly, meaning they’ll do a
three verb phrase. I don’t know what’s correct or not, you know, this is hard. It’s a hard task.
Yeah, I can actually, I’m struggling with it in my head. Well, it’s easier when you,
when you look at it, if you look at it a little easier, then listening is pretty tough. Because
you have to, because there’s no trace of it, you have to remember the words that I’m saying,
which is very hard, auditorily, we wouldn’t do it this way. We do it written, you can look at it
and figure it out. It’s easier in many dimensions in some ways, depending on the person. It’s easier
to gather written data for, I mean, most sort of psycho I work in psycholinguistics, right? Psychology
of language and stuff. And so a lot of our work is based on written stuff, because it’s so easy to
gather data from people doing written kinds of tasks. Spoken tasks are just more complicated to
administer and analyze because people do weird things when they speak. And it’s harder to analyze
what they do. But they generally point to the same kinds of things.
It’s okay. So the universal theory of language by Ted Gibson is that you can form dependency,
you can form trees from any sentences, and that’s right, you can measure the distance in some way
of those dependencies. And then you can say that most languages have very short dependencies.
All languages, all languages, all languages have short dependencies. You can actually measure that.
So a next student of mine, this guy is at University of California Irvine, Richard Futrell,
did a thing a bunch of years ago now, where he looked at all the languages we could look at,
which was about 40 initially. And now I think there’s about 60 for which there are dependency
structures. So they’re meaning there’s got to be a big text, a bunch of texts, which have been
parsed for their dependency structures. And there’s about 60 of those which have been parsed that
way. And for all of those, you can, what he did was take any sentence in one of those languages,
and you can do the dependency structure, and then start at the root. We were talking about
dependency structures. That’s pretty easy now. And he’s trying to figure out what a control
way you might say the same sentence is in that language. And so we just like, all right, there’s
a root, and it has a say as a sentence is, let’s go back to, you know, two dogs entered the room.
So entered is the root. And entered has two dependents that’s got dogs, and it has room.
Okay. And what he does is like, let’s scramble that order, that’s three things, the root and the
head and the two dependents, and into some random order, just random, and then just do that for
all the dependents down the two. So now look, do it for the, and whatever was two in dogs and for,
in room. And that’s, you know, that’s not, it’s a very short sentence. When sentences get longer,
and you have more dependents, there’s more scrambling that’s possible. And what he found,
what, so that, so, so that that’s one, you can figure out one scrambling for that sentence,
he did like a hundred times for every sentence in every corp, in every one of these texts,
every corpus. And, and then he just compared the dependency lengths in those random scramblings
to what actually happened with what the English or the French or the German was in the original
language or Chinese or what all these like 80, like, you know, 60 languages. Okay. And, and the
dependency lengths are always shorter in the real language compared to these, this kind of a control.
And there’s another, it’s a little more rigid, his control. So the way I described it, you could
have crossed dependencies, like that by scrambling that way, you could scramble in any way at all.
Languages don’t do that. They tend not to cross dependencies very much. Like, so the dependency
structure, they just, they tend to keep things non-crossed. And there’s a, you know, like,
there’s a technical term, they call that projective, but it’s just non-crossed is all that is
projective. And so if you just constrain the, the scrambling so that it only gives you projectives,
sort of non-crossed is the same thing holds. So it’s, so the, you still, still human languages are
much shorter than these, this kind of a control. So there’s like, what it means is that, that we’re,
in every language, we’re trying to put things close in relative to this kind of a control.
Like there, it doesn’t matter about the word order, some of these are verb final, some of the
means are verb, media-like English. And some are even verb initial. There are a few languages,
the world, which have VSO, world order, word order, verb, subject, object languages,
haven’t talked about those. It’s like 10% of the,
And even, even in those languages, it’s still short dependencies.
Short dependencies is rules.
Okay. So how, what, what, what are some possible explanations for that?
For why, why languages have evolved that way? So that, that’s one of the,
as opposed to disagreements you might have with Chomsky. So you consider the evolution
of language in, in terms of information theory. And for you, the purpose of language is ease of
communication, right, in processing. That’s right. That’s right. So I mean, the, the story here is just
about communication. It is just about production, really. It’s about ease of production is the story.
When you say production, can you, oh, I just mean ease of language production. It’s easier for me
to say things when the, when I’m doing, whenever I’m talking to you is somehow I’m
formulating some idea in my head and I’m putting these words together. And it’s easier for me to do
that, uh, to put, to say something where the words are close, closely connected in a dependency,
as opposed to separated, like by putting something in between and over and over again. I, it’s just
hard for me to keep that in my head. It like, that’s, that’s the whole story. Like the story,
it’s basically, it’s like the dependency grammar sort of gives that to you. Like just like long,
long as bad, short as good. It’s like easier to keep in mind because you have to keep it in mind for
probably for production, probably, you know, probably matters in comprehension as well. Like
also matters in comprehension. It’s on both sides of it. The production and the, but I would guess
it’s probably evolved for production. Like it’s about producing. It’s what’s easier for me to say
that ends up being easier for you also. I, that’s very hard to disentangle this idea of who’s it for.
Is it for me, the speaker, or is it for you, the listener? I mean, part of my language is for
you. Like the way I talk to you is going to be different from how I talk to different people.
So I’m, I’m definitely angling what I’m saying to who I’m saying, right? It’s not like I’m just
talking the same way to every single person. And so I am sensitive to my audience, but how does
that, does that, you know, work itself out in the, in the dependency link differences? I don’t
know. Maybe that’s about just the words, that part, you know, which words I select. My initial
intuition is that you optimize language for the audience. Yeah. But it’s just kind of like messing
with my head a little bit to say that some of the optimization might be, maybe the primary objective,
the optimization might be the ease of production. We have different senses, I guess. I’m, I’m like
very selfish and you’re like, I think it’s like, it’s all about me. I’m like, I’m just doing the
easiest for me at all times. I don’t want to, I’m like, I’ll, I mean, but I have to, of course,
choose the words that I think you’re going to know. I’m not going to choose words you don’t
know. In fact, I’m going to fix that when I, you know, so there it’s about, but, but maybe for,
for the syntax, for the combinations, it’s just about me. I feel like it’s, I don’t know though,
it’s very hard. Wait, wait, wait, wait, wait, wait, but the purpose of communication is to
be understood, is to convince others and so on. So like the selfish thing is to be understood.
Okay. It’s about the listener. It’s a little circular there too then. Okay. Right. I mean,
like the ease of production helps me be understood then. I don’t think it’s circular.
So I think the primary, I think the primary objective is to be understood, is about the
listener. Because otherwise, the, if you’re optimizing to, for the ease of production, then
you’re, you’re not going to have any of the interesting complexity of language. Like you’re
trying to like explain. Well, let’s control for what it is I want to say. Like I, I’m saying let’s
control for the thing, the, the message control for the message. I want to tell you, the message
needs to be understood. That’s the goal. Oh, but that’s the meaning. So I’m still talking about
the form, just the form of the meaning. How do I frame the form of the meaning is all I’m talking
about. You’re talking about a harder thing. I think it’s like, how am I like trying to change
the meaning. Let’s, let’s keep the meaning constant. Like which, if you keep the meaning constant,
how can I phrase whatever it is I need to say, like I got to pick the right words and I’m going
to pick the order so that it’s, so it’s easy for me. You know, that’s, that’s, that’s what I think
is probably like. I think I’m still tying meaning and form together in my head. But you’re saying,
if you keep the meaning of what you’re saying constant, what the optimization, yeah, it could be
the primary objective of that optimization is the, for production. That’s interesting. I’m,
I’m struggling to keep constant and meaning. It’s just so, I mean, I’m, I’m such a, I’m a human,
right? So for me, the form without having introspected on this, the form and the meaning
are tied together, like deeply because I’m a human. Like for me, when I’m speaking,
because I haven’t thought about language, like in a rigorous way about the form of language.
But look, for any event, there’s, there’s an, an unbounded, I don’t, I don’t want to say infinite,
but sort of ways of that. I might communicate that same event. This two dogs entered a room,
I can say, in many, many different ways. I can say, Hey, there’s two dogs. They entered the room.
Hey, the room was entered by something. The thing that was entered was two dogs. I mean,
there’s, I mean, it’s kind of awkward and weird and stuff. But those are all similar messages
with different forms, but different ways that might frame. And of course,
I use the same words there all the time. I could have referred to the dogs as, you know,
a Dalmatian and a Poodle or something. You know, I could have been more specific or less specific
about what they are. And I could have said, been more abstract about, about, about the number.
There’s like, so I, like, I’m trying to keep the meaning, which is this event constant. And then
how am I going to describe that to get that to you? It kind of depends on what you need to know,
right? And what I think you need to know. But I’m like, let’s control for all that stuff
and not, and, and I’m just like choosing about, I’m doing something simpler than you’re doing,
which is just forms. Yes. Just words to you specifying the species, the breed of dog and
whether they’re cute or not is changing the meaning. That might be. Yeah. Yeah. That would be
changing. Well, that would be changing the meaning for sure. Right. So you’re just, yeah. Yeah. Yeah.
That’s changing the meaning. But say, even if we keep that constant, we can still talk about what’s
easier or hard for me, right? The listener and the, and the, which phrase structures I use,
which combinations, which this is so fascinating and just like a really powerful window into human
language. But I wonder still throughout this, how vast the gap between meaning and form. I just,
I just have this, like, maybe romanticize notion that they’re close together, that they evolve
close to like hand in hand, that you can’t just simply optimize for one without the other being
in the room with us. Like it’s, well, it’s kind of like an iceberg. Form is the tip of the iceberg
and the rest, the, the meaning is the iceberg, but you can’t like separate. But I think that’s why
these large language models are so successful is because they’re good at form and form isn’t that
hard in some sense. And meaning is tough still. And that’s why they’re not, they’re, you know,
they don’t understand what they’re doing. We’re going to talk about that later maybe, but
like we can distinguish in our forget about large language models, like humans, maybe you’ll
talk about that later too, is like the difference between language, which is a communication system
and thinking, which is meaning. So language is a communication system for the meaning. It’s not
the meaning. And so that’s why, I mean, that, and there’s a lot of interesting evidence we can talk
about relevant, relevant to that. Well, I mean, that’s a really interesting question. What is the
different, what is the difference between language written, communicated versus thought?
What to use the difference between them? Well, you or anyone cast a think of a task, which they
think is, is a good thinking task. And there’s lots and lots of tasks, which should be good thinking
tasks. And whatever those tasks are, let’s say it’s, you know, playing chess, or that’s a good
thinking task, or playing some game, or doing some complex puzzles, maybe, maybe remembering
some digits that’s thinking, remembering some, a lot of different tasks we might think, maybe
just listening to music is thinking, or there’s a lot of different tasks we might think of is
thinking. There’s a woman in my department at Federico, and she’s done a lot of work on this
question about what’s the connection between language and thought. And so she uses, I was
referring earlier to MRI, fMRI, that’s her primary method. And so she has been really
fascinated by this question about whether, what language is, okay? And so as I mentioned earlier,
you can localize my language area, your language area in a few minutes, okay? In like 15 minutes,
I can listen to language, listen to non-language, or backward speech, or something. And we’ll find
areas left lateralized network in my head, which is especially, which is very sensitive to
language, as opposed to whatever that control was, okay? Can you specify what you mean by
language, like communicated language? Just sentences. You know, I’m listening to English
of any kind story, or I can read sentences, anything at all that I understand, if I understand it,
then it’ll activate my language network. So right now, my language network is going like crazy
when I’m talking, and when I’m listening to you, because we’re both, we’re communicating.
And that’s pretty stable. Yeah, it’s incredibly stable. So I’ve, I happen to be married to this
woman at Federico. So I’ve been scanned by her over and over and over since 2007 or six or something.
And so my language network is exactly the same, you know, like a month ago, as it was back in 2007.
It’s amazingly stable. It’s astounding. And with it, it’s, it’s a really fundamentally cool thing.
And so my language network is, it’s like my face, okay? It’s not changing much over time inside my
head. Can I ask a quick question? Sorry, I was a small tangent. At which point in the,
as you grow up from baby to adult, does it stabilize? We don’t know. Like that’s,
that’s a very hard question. They’re working on that right now, because of the problem scanning
little kids, like doing the, trying to do local, trying to do the, the localization on little
children in this scanner, or you’re lying in the fMRI scan, that’s the best way to figure out where
something’s going on inside our brains. And the scanner is loud and you’re in this tiny little
area, you’re claustrophobic. And it doesn’t bother me at all. I can go to sleep in there.
But some people are bothered by it. And little kids don’t really like it. And they don’t like to
lie still. And you have to be really still because you move around, that’s, that messes up the
coordinates of where, where everything is. And so, you know, try to get, you know, your question is,
how and when are language developing, you know, how, when, how does this left lateralized system
come to play? Where does it, you know, and it’s really hard to get a two year old to do this task.
But you can maybe, they’re starting to get three and four and five year olds to do this task for
short periods. And it looks like it’s there pretty early. So clearly, when you lead up to your, like,
a baby’s first words, before that, there’s a lot of fascinating turmoil going on about like figuring
out like, what are, what are these people saying? Yeah. And you’re trying to like make sense. How
does that connect to the world? And all that kind of stuff. Yeah, that might be just fascinating
development that’s happening there. That’s hard to introspect. But anyway, you,
we’re back to the scanner. And I can find my network in 15 minutes. And now we can ask a,
we can ask, find my network, find yours, find, you know, 20 other people do this task.
And we can do some other tasks. Anything else you think is thinking of some other thing. I can
do a spatial memory task. I can do a music perception task. I can do programming task,
if I program, okay, I can do what, where I can like understand computer programs. And
none of those tasks will tap the language network at all, like at all. There’s no overlap. They’re,
they’re highly activated in other parts of the brain. There’s a, there’s a bilateral network,
which I think she tends to call the multiple demands network, which does anything kind of hard. And,
and so anything that’s kind of difficult in some ways will activate that multiple demands network.
I mean, music will be in some music area, you know, there’s music specific kinds of areas. And so,
but they’re, but, but none of them are activating the language area at all, unless there’s words.
Like, so if you have music and there’s a song and you can hear the words, then then you get the
language area. We’re talking about speaking and listening, but are, or are we also talking about
reading? This is all comprehension of any kind. And so, that is fast. So what this, this, this
network doesn’t make any difference if it’s written or spoken. So the, the, the thing that she calls,
Federico calls the, the language network is this high level language. So it’s not about the spoken,
the spoken language, and it’s not about the written language. It’s about either one of them.
And so we’re, so when you do speech, you’re sort of listed, you either, you’re listening to speech,
and you’d, you’d, you’d subtract away some language you don’t understand. And so, or you
subtract away back, backward speech, which signs, sounds like speech, but it isn’t. And, and then,
so you take away the sound part altogether. And so, and then if you do written, you get exactly
the same network. So for just reading the language versus reading sort of nonsense words or something
like that, you’ll find exactly the same network. And so it’s just about high level,
the comprehension of language. Yeah. In this case, and the same thing happened,
production’s a little harder to run the scanner, but the same thing happens in production. You get
the same network. So production’s a little harder. You have to figure out how do you run a task,
you know, in the network such that you’re doing some kind of production. And I can’t remember
what, they’ve done a bunch of different kinds of tasks there where you get people to, you know,
produce things. Yeah. Figure out how to produce. And the same network
goes on there. Exactly the same place. And so if, wait, wait, so if you read random words.
Yeah. If you read things like, um, like gibberish. Yeah. Yeah. Lewis Carroll’s,
it was brilliant. Jabberwocky, right? They call that Jabberwocky speech.
The network doesn’t get activated. Not as much. There are words in there.
Yeah. Because it’s like, there’s, there’s function words and stuff. So it’s lower
activation. Yeah. Yeah. So there’s like, basically the more language like it is, the higher it goes
in the language network. And that network is there from when you speak from as soon as you
learn language. And, and it’s, it’s there. Like you speak multiple languages, the same network
is going for your multiple languages. So you speak English, you speak Russian,
both of them are hitting that same network. If you, if you’re fluent in those languages.
So programming. Not at all. Isn’t that amazing? Even if you’re a really good programmer,
that is not a human language. It’s just not conveying the same information. And so it is
not in the language network. And so that has mind blowing as I think that’s pretty cool.
That’s weird. It is amazing. And so that’s like one set of day. This is hers like shows that
what you might think is thinking is, is not language. Language is just the seek, just,
just this conventionalized system that we’ve worked out in human languages. Oh, another fascinating
little bit tidbit is that even if they’re these constructed languages like Klingon or I don’t
know the languages from Game of Thrones, I’m sorry. I don’t remember those languages. Maybe
a lot of people offended right now. There’s people that speak those languages. They really
speak those languages because the people that wrote the languages for the shows,
they did an amazing job of constructing on something like a human language. And those,
that, that lights up the language area. That’s like, because they can speak, you know,
pretty much arbitrary thoughts in a human language. It’s not a, it’s a constructed human
language. Probably it’s related to human languages because the people that were constructing them
wasn’t were making them like human languages in various ways, but it also activates the same
network, which is pretty, pretty cool. Anyway, sorry to go into a place where you may be
a little bit philosophical, but is it possible that this area of the brain is doing some kind
of translation into a deeper set of almost like concepts? It has to be doing. So it’s
doing in communication, right? It is translating from thought, whatever that is, is more abstract,
and it’s doing that. That’s what it’s doing. Like it is, that is kind of what it is doing.
It’s kind of a meaning network, I guess. Yeah, like a translation network.
Yeah. But I wonder what is at the core at the bottom of it? Like what are thoughts? Are they,
thoughts, to me, like thoughts and words, are they neighbors or are, is it one turtle sitting
on top of the other? Meaning like, is there a deep set of concepts that we… Well, there’s
connections right between what these things mean and then there’s probably other parts of the brain
that what these things mean. And so when I’m talking about whatever it is I want to talk about,
it’ll be represented somewhere else. That knowledge of whatever that is will be represented
somewhere else. Well, I wonder if there’s like some stable, nicely compressed encoding of meanings
that’s separate from language. I guess the implication here is that we don’t think in
language. That’s correct. Isn’t that cool? And that’s so interesting. So people, I mean,
this is like hard to do experiments on, but there is this idea of an inner voice and a lot of people
have an inner voice. And so if you do a poll on the internet and ask if you hear yourself talking
when you’re just thinking or whatever, about 70 or 80% of people will say yes. Most people
have an inner voice. I don’t. And so I always find this strange. So when people talk about an
inner voice, I always thought this was a metaphor. And they hear, I know most of you, whoever’s
listening to this thinks I’m crazy now because I don’t have an inner voice and I just don’t know
what you’re listening to. It sounds so kind of annoying to me, but to have this voice going on
while you’re thinking, but I guess most people have that. And I don’t have that. And I don’t,
we don’t really know what that connects to. I wonder if the inner voice activates that same
network. I don’t know. I don’t know. I don’t know. I mean, this could be speachy, right? So that’s
like, do you hear, do you have an inner voice? I don’t think so. A lot of people have this sense
that they hear themselves and then say they read someone’s email. I’ve heard people tell me that
they hear that other person’s voice when they read other people’s emails. And I’m like, wow,
that sounds so disruptive. I do think I like vocalize what I’m reading, but I don’t think I hear a
voice. Well, that’s, you probably don’t have an inner voice. Yeah, I don’t think I have an inner voice.
People have an inner voice. People have this strong percept of hearing sound in their heads
when they’re just thinking. I refuse to believe that’s the majority of people. Majority, absolutely.
What? It’s like two thirds or three quarters. It’s a lot. I would never ask class. And I went
internet. They always say that. So you’re in a minority. It could be a self report flaw.
It could be. You know, when I’m reading inside my head, I’m kind of like saying the words,
which is probably the wrong way to read, but I don’t hear a voice. There’s no press,
percept of a voice. I refuse to believe the majority people have. Anyway, it’s a fascinating,
the human brain is fascinating, but it still blew my mind that the, that language does appear,
comprehension does appear to be separate from thinking. So that’s one set. One set of data
from Fedorenko’s group is that no matter what task you do, if it doesn’t have words and combinations
of words in it, then it won’t light up the language network. And, you know, you could, it’ll be active
somewhere else, but not there. So that’s one. And then this other piece of evidence relevant
to that question is, it turns out there are these, this group of people who’ve had a massive stroke
on the left side and wiped out their language network. And as long as they didn’t wipe out
everything on the right as well, in that case, they wouldn’t be, you know, cognitively functionable.
But if they just wiped out language, which is pretty tough to do because it’s,
it’s very expansive on the left. But if they have, then there are these, there’s patients
like this called so-called global aphasics who can do any task just fine, but not language.
They can’t, you can’t talk to them. I mean, they don’t understand you. They can’t speak,
can’t write, they can’t read, but they can do, they can play chess, they can drive their cars,
they can do all kinds of other stuff, you know, do math, they can do all, like, so math is not
in the language area, for instance, you do arithmetic and stuff. That’s not language area.
It’s got symbols. So people sort of confuse some kind of symbolic processing with language. And
symbolic processing is not the same. So there are symbols and they have meaning, but it’s not
language. It’s not a, you know, conventionalized language system. And so language, so math isn’t
there. And so they can do math. They do just as well as their control, age match controls and
all these tasks. This is Rosemary Varley over in University College London, who has a bunch of
patients who she’s shown this that they’re just, so that sort of combination suggests that language
isn’t necessary for thinking. It doesn’t mean that you can’t think in language. You could think
in language because language allows a lot of expression, but it’s just, you don’t need it
for thinking. It suggests that language is separate, is a separate system.
This is kind of blowing my mind right now. It’s cool, isn’t it? I’m trying to load that in
because it has implications for large language models. It sure does. And they’ve been working
on that. Well, let’s take a stroll there. You wrote that the best current theories of human
language are arguably large language models. So this has to do with form. It’s kind of a big
theory. And, but the reason it’s arguably the best is that it does the best at predicting
what’s English, for instance. It’s, it’s like incredibly good, you know, it better than any
other theory. It’s so, you know, but, you know, we don’t, you know, there’s, it’s not sort of,
there’s not enough detail. It’s opaque. Like there’s not, you don’t know what’s going on.
You know what’s going on. It’s another black box. But I think it’s, you know, it is a theory.
What’s your definition of a theory? Because it’s a gigantic, it’s a gigantic black box with,
you know, a very large number of parameters controlling it. To me, theory usually requires
a simplicity, right? Well, I don’t know. Maybe I’m just being loose there. I think it’s a,
it’s not, it’s not a great theory, but it’s a theory. It’s a good theory in one sense in that
it covers all the data. Like anything you want to say in English, it does. And so that’s why it’s,
that’s how it’s arguably the best is that no other theory is as good as a large language model in
predicting exactly what’s good and what’s bad in English. Now you’re saying, is it a good theory?
Well, probably not, you know, because I want a smaller theory than that. It’s too big. I agree.
You could probably construct a mechanism by which it can generate a simple explanation
of a particular language, like a set of rules, something like it could generate a dependency
grammar for a language, right? Yeah. You could probably, you could probably just ask it about
it. Well, you know, that’s, I mean, that presumes, and there’s some evidence for this that some
large language models are implementing something like dependency grammar inside them. And so
there’s work from a guy called Chris Manning and colleagues over at Stanford in natural language.
And they looked at, I don’t know how many large language model types, but certainly Burt and
some others, where you do some kind of fancy math to figure out exactly what kind of abstractions
of representations are going on. And they were saying it does look like dependency structure is
what they’re constructing. It doesn’t, like so it’s actually a very, very good map. So kind of a,
they are constructing something like that. Does it mean that, you know, that they’re using that
for meaning? I mean, probably, but we don’t know. You write that the kinds of theories of language
that LLMs are closest to are called construction based theories. Can you explain what construction
based theories are? It’s just a general theory of language such that there’s a form and a meaning
pair for, for lots of pieces of the language. And so it’s, it’s, it’s primarily usage based is a
construction grammar. It’s just, it’s trying to deal with the things that people actually say,
actually say and actually write. And so that’s, it’s a usage based idea. And what’s the constructional
construction is either a simple word, so of like a morpheme plus its meaning or a combination of
words, it’s basically combinations of words, like the rules. So, but it’s, it’s, it’s
un, un specified as to what the form of the grammar is under underlying Lee. And so I would, I would
argue that the dependency grammar is maybe the right form to use for the types of construction
grammar. Construction grammar typically isn’t kind of formalized quite. And so maybe the formalization,
a formalization of that, it might be in dependency grammar. I mean, I, I would think so. But I mean,
it’s up to people, other researchers in that area, if they agree or not. So.
Do you think that large language models understand language? Are they mimicking language? I guess
the deeper question there is, are they just understanding the surface form? Or do they
understand something deeper about the meaning that then generates the form?
I mean, I would argue they’re doing the form. They’re doing the form, they’re doing it really,
really well. And are they doing the meaning? No, probably not. I mean, there’s lots of these
examples from various groups showing that they can be tricked in all kinds of ways. They really
don’t understand the, the meaning of what’s going on. And so there’s a lot of examples that he and
other groups have given, which just, which show they don’t really understand what’s going on.
So, you know, the Monty Hall problem is this silly problem, right? Where, you know, if you
have three door, it’s less make a deal as this old game show. And there’s three doors, and there’s
a prize behind one, and there’s some junk prizes behind the other two, and you’re trying to select
one. And if you, you know, he knows Monty, he knows where the target item is, the good thing.
He knows everything is back there. And you’re supposed to, he gives you a choice. You choose
one of the three. And then he opens one of the doors, and it’s some junk prize. And then the
question is, should you trade to get the other one? And, and the answer is yes, you should trade,
because he knew which ones you could turn around. And so now the odds are two thirds, okay.
And then you just change that a little bit to the large language mall, the large language malls,
seeing that, that, that explanation so many times that it just, if you change the story, it’s a
little bit, but it makes it sound like it’s the Monty Hall problem, but it’s not. You just say,
oh, there’s three doors and one behind them is a good prize. There’s two bad doors. I happen to
know it’s behind door number one. The good prize, the car is behind door number one. So I’m going
to choose door number one. Monty Hall opens door number three and shows me nothing there. Should
I trade for door number two? Even though I know the good prize in door number one, and then the
large language malls say, yes, you should trade because it’s a, it’s, it just goes through the,
the, the, the forms that it’s seen before so many times on these cases where it, yes, you
should trade because, you know, your odds have shifted from one in three now to two out of three
to being that thing. It doesn’t have any way to remember that actually you have 100% probability
behind that door number one. You know that. That’s not part of the, of the, the scheme that it’s seen
hundreds and hundreds of times before. And so you can’t, you can’t, even if you try to explain to
it that it’s wrong, that they can’t do that. It’ll just keep giving you back the, the problem.
But it’s also possible the larger language model would be aware of the fact that there’s sometimes
over a representation of a, of a particular kind of formulation. And it’s easy to get tricked by
that. And so you could see if they get larger and larger models be a little bit more skeptical.
So you see a over representation. So like you, it just feels like form can,
training on form can go really far in terms of being able to generate things that look like
the thing understands deeply the underlying world, world model of the kind of mathematical world,
physical world, psychological world that would generate these kinds of sentences.
It just feels like you’re creeping close to the meaning part, easily fooled, all this kind of
stuff, but that’s humans too. So it just seems really impressive how often it seems like it
un-understands concepts. I mean, you don’t have to convince me of that. I’m, I am very,
very impressed, but does it, does do, I mean, you’re, you’re giving a possible world where maybe
someone’s going to train some other versions such that it’ll be somehow abstracting away from types
of forms. I mean, I don’t think that’s happened. And so, well, no, no, no, no, I’m not saying that.
I think when you just look at anecdotal examples and just showing a large number of them where it
doesn’t seem to understand and it’s easily fooled, that does not seem like a scientific,
the data driven like analysis of like how many places is a damn impressive in terms of meaning
and understanding and how many places is easily fooled. And like that’s not the inference. So I
don’t want to make that, the inference I don’t, I wouldn’t want to make was that inference. The
inference I’m trying to push is just that is it, is it like humans here? It’s probably not like
humans here. It’s different. So humans don’t make that error. If you explain that to them,
they’re not going to make that error. You know, they don’t make that error. And so that’s something,
it’s doing something different from humans that they’re doing in that case.
What’s the mechanism by which humans figure out that it’s an error?
I’m just saying the error there is like, if I explain to you, there’s 100% chance
that the car is behind this case, this door, well, do you want to trade? If you’ll say no.
But this thing will say yes, because it’s so, that trick, it’s so wound up on the form
that it’s, that’s an error that a human doesn’t make, which is kind of interesting.
Less likely to make, I should say.
Yeah, less likely.
Because like humans are very…
Oh yeah. I mean, you’re asking, you know, you’re asking humans to, you’re asking a system to
understand 100%, like you’re asking some mathematical concepts. And so like…
Look, the places where large language models are, the form is amazing. So let’s go back to nested
structures, center embedded structures. Okay. If you ask a human to complete those, they can’t do it.
Neither can a large language model. They’re just like humans in that. If you ask, if I ask a large
language model… That’s fascinating, by the way.
That central embedding, the central embedding struggles with…
Just like humans, exactly like humans. Exactly the same way as humans. And that’s not trained.
So they do exactly… So that is the similarity. So, but then it’s, that’s not meaning, right?
This is form. But when we get into meaning, this is where they get kind of messed up.
When you start to saying, oh, what’s behind this door? Oh, it’s, you know, this is the thing I want.
Humans don’t mess that up as much. You know, here, the form is, it’s just like the form of the match
is amazing. It’s similar without being trained to do that. I mean, it’s trained in the sense
that it’s getting lots of data, which is just like human data, but it’s not being trained on,
you know, bad sentences and being told what’s bad. It just can’t do those. It’ll actually
say things like, those are too hard for me to complete or something, which is kind of interesting.
Actually kind of, how does it know that? I don’t know. But it really often doesn’t just
complete, very often says stuff that’s true and sometimes says stuff that’s not true.
And almost always the form is great. But it’s still very surprising that with really great
form, it’s able to generate a lot of things that are true based on what is trained on and so on.
So it’s not just form that is generating. It’s mimicking true statements from the internet.
I guess the underlying idea there is that on the internet, truth is overrepresented versus
falsehood. I think that’s probably right. Yeah. So, but the fundamental thing is trained on,
you’re saying is just form. I think so. Yeah, I think so. Well, that’s a sad, if that’s, to me,
that’s still a little bit of open question. I probably lean agreeing with you, especially
now you just blown my mind that there’s a separate module in the brain for language versus thinking.
Maybe there’s a fundamental part missing from the large language model approach
that lacks the thinking, the reasoning capability. Yeah, that’s what this group argues. So the same
group, Federenko’s group, has a recent paper arguing exactly that. There’s a guy called Kyle
Mahwell who’s here in Austin, Texas, actually. He’s an old student of mine, but he’s a faculty
in linguistics at Texas. And he was the first author on that. That’s fascinating. Still,
to me, an open question. Yeah. What do you have the interesting limits of LLMs?
You know, I don’t see any limits to their form. Their form is perfect. Impressive.
Yeah, it’s pretty much, I mean, it’s close to… Well, you said ability to complete central
embeddings. Yeah, it’s just the same as humans. It seems the same as humans. But that’s not
perfect, right? That’s good. No, but I want to be like humans. I’m trying to, I want a model of
humans. Oh, wait, wait, wait, wait. Oh, so perfect is as close to humans as possible. I got it. Yeah.
But you should be able to, if you’re not human, you’re like you’re superhuman, you should be able
to complete central embedded sentences, right? I mean, that’s the mechanism is, if it’s modeling
some, I think it’s kind of really interesting that it’s more like, like I think it’s potentially
underlyingly modeling something like what the way the form is processed. The form of human language.
The way that you… And how humans process the language. Yes. Yes. I think that’s plausible.
And how they generate language. Process language and general language, that’s fascinating.
So in that sense, they’re perfect. If we can just linger on the center embedding
thing. That’s hard for LLM’s produce. And that seems really impressive because that’s hard for
humans to produce. And how does that connect to the thing we’ve been talking about before,
which is the dependency grammar framework in which you view language and the finding that
short dependencies seem to be a universal part of language. So why is it hard to complete center
embeddings? So what I like about dependency grammar is it makes the cognitive cost associated
with longer distance connections very transparent. Basically, there’s some… It turns out there is
a cost associated with producing and comprehending connections between words, which are just not
beside each other. The further apart they are, the worse it is that according to… Well,
we can measure that. And there is a cost associated with that. Can you just linger on what do you
mean by cognitive cost? Sure. And how do you measure it? Oh, well, you can measure it in a lot
of ways. The simplest is just asking people to say whether… How good a sentence sounds.
We just ask… That’s one way to measure. And you try to triangulate then across sentences and
across structures to try to figure out what the source of that is. You can look at reading times
in controlled materials and certain kinds of materials. And then we can measure the
dependency distances there. There’s a recent study which looked at… We’re talking about
the brain here. We could look at the language network. We could look at the language network
and we could look at the activation in the language network and how big the activation
is depending on the length of the dependencies. And it turns out in just random sentences that
you’re listening to. If you’re listening to… So it turns out there are people listening to stories
here. And the longer the dependency is, the stronger the activation in the language network.
And so there’s some measure… There’s a different… There’s a bunch of different measures we could
do. That’s a kind of a neat measure actually of actual… Activations. Activation in the brain.
So you can somehow in different ways convert it to a number. I wonder if there’s a beautiful
equation connecting cognitive costs and length of dependency. E equals MC squared kind of thing.
Yeah. It’s complicated, but probably it’s doable. I would guess it’s doable. I tried to do that a
while ago and I was reasonably successful, but for some reason I stopped working on that. I
agree with you that it would be nice to figure out… So there’s some way to figure out the cost.
I mean, it’s complicated. Another issue you raised before was how do you measure distance?
Is it words? It probably isn’t. Is it part of the problem? Is that some words matter
than more than others? And probably… Meaning nouns might matter depending… And then it maybe
depends on which kind of noun. Is it a noun we’ve already introduced or a noun that’s already been
mentioned? Is it a pronoun versus a name? All these things probably matter. So probably the
simplest thing to do is just like, “Oh, let’s forget about all that and just think about words
or more themes.” For sure, but there might be some insight in the kind of function that fits
the data, meaning quadratic. I think it’s an exponential. We think it’s probably an exponential
such that the longer the distance, the less it matters. And so then it’s the sum of those.
That was our best guess a while ago. So you’ve got a bunch of dependencies. If you’ve got a
bunch of them that are being connected at some point, at the ends of those, the cost is some
exponential function of those, is my guess. But because the reason it’s probably an exponential
is it’s not just the distance between two words. Because I can make a very, very long subject,
verb depends by adding lots and lots of noun phrases and prepositional phrases. And it doesn’t
matter too much. It’s when you do nest it, when I have multiple of these, then things
get go really bad, go south. That’s probably somehow connected to working memory or something like
this. Yeah, that’s probably the function of the memory here is the access, is trying to find those
earlier things. It’s kind of hard to figure out what was referred to earlier, those are those
connections. That’s the sort of notion of working, as opposed to a storagey thing, but trying to
connect, retrieve those earlier words depending on what was in between. And then we’re talking about
interference of similar things in between. That’s the right theory probably has that kind of notion
and it is an interference of similar. And so I’m dealing with an abstraction over the right theory,
which is just, let’s count words, it’s not right, but it’s close. And then maybe you’re right though,
there’s some sort of an exponential or something to figure out the total so we can figure out a
function for any given sentence in any given language. But it’s funny, people haven’t done
that too much, which I do think is, I’m interested that you find that interesting. I really find
that interesting. And a lot of people haven’t found it interesting. And I don’t know why I haven’t
got people to want to work on that. I really like that too. That’s a beautiful. And the underlying
idea is beautiful that there’s a cognitive cost that correlates with the length of dependency.
It feels like language is so fundamental to the human experience. And this is a nice clean
theory of language where it’s like, wow, okay. So we like our words close together,
dependent words close together. That’s why I like it too. It’s so simple.
Yeah, the simplicity of the theory. And yet it explains some very complicated phenomena.
If I write these very complicated sentences, it’s kind of hard to know why they’re so hard.
And you can like, oh, nail it down. I can give you a math formula for why each one
of them is bad and where. And that’s kind of cool. I think that’s very neat.
Have you gone through the process? Is there like a, if you take a piece of text and then simplify
sort of like there’s an average length of dependency and then you like,
you know, reduce it and see comprehension on the entire, not just a single sentence, but
like, you know, you go from James Joyce to Hemingway or something.
No, no, simple answer is no. There’s probably things you can do in that kind of direction.
That’s fun. We might, you know, we’re going to talk about legalese at some point.
And so maybe we’ll talk about that kind of thinking with applied to legalese.
Well, let’s talk about legalese because you mentioned that as an exception,
which is taking a tangent upon tangent. That’s an interesting one. You give it as an exception.
It’s an exception.
That you say that most natural languages, as we’ve been talking about,
have local dependencies with one exception, legalese.
That’s right.
So what is legalese, first of all?
Oh, well, legalese is what you think it is. It’s just any legal language.
I mean, like I actually know very little about the kind of language that lawyers use.
So I’m just talking about language in laws and language in contracts.
So the stuff that you have to run into, we have to run into every other day or every day
and you skip over because it reads poorly and or, you know, partly it’s just long, right?
There’s a lot of text there that we don’t really want to know about.
And so, but the thing I’m interested in, so I’ve been working with this guy called
Eric Martinez, who is a, he was a lawyer who was taking my class.
I was teaching a psycholinguistics lab class and I have been teaching it for a long time
at MIT and he’s a, he was a law student at Harvard and he took the class because he had
done some linguistics as an undergrad and he was interested in the problem of why legalese
sounds hard to understand, you know, why and so why is it hard to understand
and why do they write that way if it is hard to understand.
It seems apparent that it’s hard to understand.
The question is why is it?
And so we didn’t know and we did an evaluation of a bunch of contracts.
Actually, we just took a bunch of sort of random contracts because I don’t know,
you know, there’s contracts and laws might not be exactly the same, but
contracts are kind of the things that most people have to deal with most of the time.
And so that’s kind of the most common thing that humans have,
like humans, that adults in our industrialized society have to deal with a lot.
And so that’s what we pulled and we didn’t know what was hard about them,
but it turns out that the way they’re written is very center embedded,
has nested structures in them.
So it has low frequency words as well.
That’s not surprising.
Lots of texts have low, it does have surprising,
slightly lower frequency words than other kinds of control texts,
even sort of academic texts.
Legalese is even worse.
It is the worst that we weren’t being able to find.
You just reveal the game that lawyers are playing.
They’re optimizing it different.
Well, you know, it’s interesting.
That’s like, now you’re getting at why.
And so, and I don’t think, it’s on your thing, they’re doing intentionally.
I don’t think they’re doing intentionally.
But let’s, let’s, let’s get to it.
It’s an emergent phenomena.
Yeah, yeah, yeah.
We’ll get to that.
We’ll get to that.
And so, but we wanted to see why, so we see what first as opposed.
So like, it turns out that we’re not the first to observe that legalese is weird.
Like back to Nixon had a plain language act in 1970 and, and Obama had one.
And boy, a lot of these, you know, a lot of her presidents have said,
oh, we’ve got to simplify legal language, must simplify.
But if you don’t know how it’s complicated, it’s not easy to simplify it.
You need to know what it is you’re supposed to do before you can fix it.
Right.
And so you need to like, you need a cycle linguist to analyze the text and see what’s
wrong with it before you can like fix it.
You don’t know how to fix it.
How am I supposed to fix something?
I don’t know what’s wrong with it.
And so what we did was just, that’s what we did.
We figured out, well, that’s okay.
We just had a bunch of contracts, had people, and we encoded them for the bunch of features.
And so another feature of the people, one of them was the center embedding.
And so that is like basically how often a, a clause would, would, would intervene between
a subject and a verb, for example, that’s one kind of a center embedding of a clause.
Okay.
And turns out they’re massively center embedded.
Like, so I think in random contracts and in random laws, I think you get about 70% or
80, something like 70% of sentences have a center embedded clause, which is insanely high.
If you go to any other text, it’s down to 20% or something.
It’s, it’s, it’s so much higher than any control you can think of, including, you think, oh,
people think, oh, technical, um, academic texts.
No, people don’t write center embedded sentences in, in technical academic texts.
I mean, they do a little bit, but much, it’s, it’s on the 20%, 30% realm,
as opposed to 70.
And so, and so there’s that, and, and there’s low frequency words.
And then people, oh, maybe it’s passive.
People don’t like the passive, passive, for some reason, the passive voice in English
has a bad rap.
And I’m not really sure where that comes from.
And, and there is a lot of passive in the, there’s much more passive voice in the, in the,
in legalese than there is in other texts.
And the passive voice accounts for some of the low frequency words.
No, no, no, no, those are separate.
Those are separate.
Oh, so passive voice sucks.
That’s really easy.
Low frequency word sucks.
Well, sucks are different.
So these are different.
That’s a judgment on passive.
Yeah, yeah, yeah, pass the, drop the judgment.
It’s just like, these are frequent.
These are things which happen in legalese texts.
Then we can ask the dependent measure is like,
how well you understand those things with those features.
Okay.
And so then, and it turns out the passive makes no difference.
So it has a zero effect on your comprehension ability, on your recall ability.
No, nothing at all.
That means no effect.
Your, the words matter a little bit.
They do low frequency words are going to hurt you in recall and understanding.
But what really, what really hurts is the central embedding.
That kills you.
That is like, that slows people down.
That makes them, that makes them very, very poor at understanding.
That makes them, they, they, they can’t recall what was said as well, nearly as well.
And we, we did this not only on lay people.
We didn’t have a lot of lay people.
We ran it on a hundred lawyers.
We recruited lawyers from a, from a wide range of, of sort of different levels
of law firms and stuff.
And they have the same pattern.
So they also, like, when, when, when they did this, I did not know it happened.
I thought maybe they could process, they’re used to legally.
So they can process it just as well as it was normal.
No, no, they, they, they’re much better than lay people.
So they’re much, like, they can much better recall, much better understanding,
but they have the same main effects as, as, as lay people, as lay people, exactly the same.
So they also much prefer the non-centered.
So we, we, we constructed non-centered embedded versions of each of these.
We constructed versions which have higher frequency words in those places.
And we, we did, we un-un-un-passivized, we turned them into active versions.
The passive active made no difference.
The words made a little difference.
And the un-centered embedding makes, makes big differences in all the populations.
Un-centered embedding.
How hard is that process, by the way?
Not very hard.
The society don’t question, but how hard is it to detect center embedding?
Oh, easy, easy to detect.
You’re just looking at long dependencies, or is there a real?
You can just, you can, so there’s automatic parsers for English, which are pretty good.
And they can detect center embedding.
Oh yeah.
Very.
Or, I guess, nested.
Perfectly.
Yeah, you, you’ve learned, yeah, pretty much.
So you, you’re not just looking for long dependencies.
You’re just literally looking for center embedding.
Yeah, yeah, we are in this case, in these case, but long dependencies are,
they’re highly correlated.
So like a center embedding is a, is a big bomb you throw inside, inside of a sentence
that just blows up the, that, that makes.
Yeah, yeah.
Can I read a sentence for you from these things?
Sure.
I see, I can find, I mean, this is just like one of the things that,
this is just.
My eyes, my glaze over in middle, mid sentence.
No, I understand that.
I mean, legalese is hard.
This is a go, because in the event that any payment or benefit by the company,
all such payments and benefits, including the payments and benefits under section 3a
here of being here at, here and after referred to as a total payment,
would be subject to the excise tax, then the cash severance payments shall be reduced.
So that’s something we pulled from a regular text, from a, from a contract.
Wow.
And, and, and the center embedded bit there is just, for some reason, there’s a definition.
They throw the definition of what payments and benefits are in between the subject and the verb.
Let’s, how about don’t do that?
Yeah.
How about put the definition somewhere else, as opposed to in the middle of the sentence.
And so that’s, that’s very, very common, by the way.
That’s, that’s what happens.
So you just throw your definitions, you use a word, a couple words, and then you define it,
and then you continue the sentence.
Like just don’t write like that.
And, and you ask, so when we asked lawyers, we thought, oh, maybe lawyers like this.
Lawyers don’t like this.
They don’t like this.
They don’t want to, they don’t want to write like this.
They, they, we asked them to rate materials which are with the same meaning
with, with uncentred bed and center bed, and they much preferred the uncentred bed versions.
On the comprehension, on the reading side.
Yeah.
Well, and we asked them, we asked them, would you hire someone who writes like this or this?
We asked them all kinds of questions.
And they always preferred the less complicated version, all of them.
So I don’t even think they want it this way.
Yeah, but how did it happen?
How did it happen?
That’s a very good question.
And, and the answer is, they still don’t know.
But I have some theories.
Well, our, our best theory at the moment is that there’s, there’s actually some kind of a
performative meaning in the center embedding, in the style which tells you it’s legalese.
We think that that’s the kind of a style which tells you it’s legalese.
Like that’s a, it’s a reasonable guess.
And maybe it’s just, so for instance, if you’re like, it’s like,
a magic spell.
So we kind of call this the magic spell hypothesis.
So when you give them, when you tell someone to put a magic spell on someone, what do you do?
They, you know, people know what a magic spell is and they, they do a lot of rhyming.
You know, that’s, that’s kind of what people will tend to do.
They’ll do rhyming and they’ll do sort of like some kind of poetry kind of thing.
Abracadabra type of thing.
Yeah.
And maybe that’s, there’s a syntactic sort of a reflex here of a, of a magic spell,
which is center embedding.
And so that’s like, oh, it’s trying to like tell you this is like, this is something which is true,
which is what the goal of law, law is, right?
Is telling you something that we want you to believe as certainly true, right?
That’s, that’s what legal contracts are trying to enforce on you, right?
And so maybe that’s like a form which has, this is like an abstract, very abstract form,
center embedding, which has a, has a, has a meaning associated with it.
Well, don’t you think there’s an incentive
for lawyers to generate things that are hard to understand?
That was our, one of our working hypotheses.
We just couldn’t find any evidence of that.
No, lawyers also don’t understand it.
But you’re creating space.
Why you yourself, but I mean, you ask in a communist Soviet union, the individual members,
their self-report is not going to correctly reflect what is broken about the gigantic bureaucracy
that leads to Chernobyl or something like this.
I think the incentives under which you operate are not always transparent
to the members within that system.
So like, it just feels like a strange coincidence that like, there is benefit
if you just zoom out, look at the system, as opposed to asking individual lawyers
that making something hard to understand is going to make a lot of people money.
Yeah.
Like there’s going to, you’re going to need a lawyer
to figure that out, I guess, from the perspective of the individual.
But then that could be the performative aspect.
It could be as opposed to the incentive driven to be complicated.
It could be performative to where we lawyers speak in this sophisticated way
and you regular humans don’t understand it, so you need to hire a lawyer.
Yeah, I don’t know which one it is, but it’s suspicious.
Suspicious that it’s hard to understand and everybody’s eyes glaze over and they don’t read.
I’m suspicious as well.
I’m still suspicious and I hear what you’re saying.
It could be kind of a no individual and even average of individuals.
It could just be a few bad apples in a way which are driving the effect in some way.
Influential bad apples at the sort of, that everybody looks up to,
whatever their like central figures and how, you know.
But it turns out, but it is kind of interesting that among our hundred lawyers,
they did not share that.
They didn’t want this, that’s fascinating.
They really didn’t like it.
And they weren’t better at than regular people at comprehending it.
Or they were on average better, but they had the same difference.
The exact same difference.
But they wanted it fixed.
And so that gave us hope that because it actually isn’t very hard to construct a material,
which is uncenter embedded and has the same meaning, it’s not very hard to do.
Just basically in that situation, just putting definitions outside of the subject
verb relation in that particular example, and that’s kind of, that’s pretty general.
What they’re doing is just throwing stuff in there, which you didn’t have to put in there.
There’s extra words involved.
Typically, you may need a few extra words sort of to refer to the things that you’re
defining outside in some way, because if you only use it in that one sentence,
then there’s no reason to introduce extra terms.
So we might have a few more words, but it’ll be easier to understand.
So, I mean, I have hope that now that maybe we can make legalese less convoluted in this way.
So maybe the next president in the United States can, instead of saying generic things,
say, “I ban center embeddings and make Ted the language czar of the U.S.”
Like Eric Martinez is the guy you should really put in there.
Eric Martinez, yeah, yeah, yeah.
But center embeddings are the bad thing to have.
That’s right.
So you can get rid of that.
That’ll do a lot of it.
That’ll fix a lot.
That’s fascinating.
That is so fascinating.
And it’s just really fascinating on many fronts that humans are just not able to
deal with this kind of thing.
And that language, because of that involved in the way you did, it’s fascinating.
So one of the mathematical formulations you have when talking about languages
communication is this idea of noisy channels.
What’s a noisy channel?
So that’s about communication.
And so this is going back to Shannon.
So Shannon, Claude Shannon was a student at MIT in the ’40s.
And so he wrote this very influential piece of work about communication theory or information
theory.
And he was interested in human language, actually.
He was interested in this problem of communication, of getting a message from
my head to your head.
And so he was concerned or interested in what was a robust way to do that.
And so assuming we both speak the same language, we both already speak English,
whatever the language is, we speak that.
What is a way that I can say the language so that it’s most likely to get the signal
that I want to you.
And so and then the problem there in the communication is the noisy channel.
Is that there’s a lot of noise in the system.
I don’t speak perfectly.
I make errors.
That’s noise.
There’s background noise.
You know that.
Like a literal background noise.
There is like white noise in the background or some other kind of noise.
There’s some speaking going on that you’re at a party.
That’s background noise.
You’re trying to hear someone.
It’s hard to understand them because there’s all those other stuff going on in the background.
And then there’s noise on the receiver side so that you have some problem maybe understanding
me for stuff that’s just internal to you in some way.
So you’ve got some other problems, whatever, with understanding for whatever reasons.
Maybe you’ve had too much to drink.
You know, who knows why you’re not able to pay attention to the signal.
So that’s the noisy channel.
And so that language, if it’s communication system, we are trying to optimize in some sense
the passing of the message from one side to the other.
And so I mean, one idea is that maybe, you know, aspects of like word order,
for example, might have optimized in some way to make language a little more easy
to be passed from speaker to listener.
And so Shannon’s the guy that did the stuff way back in the forties.
You know, it’s very interesting, you know, historically, he was interested in working
in linguistics.
He was in MIT and he did, this is his master’s thesis of all things.
You know, it’s crazy how much he did for his master’s thesis in 1948, I think,
or ’49 or something.
And he wanted to keep working in language and it just wasn’t a popular communication
as a reason, a source for what language was, wasn’t popular at the time.
So Chomsky was becoming, it was moving in there.
He was, and he just wasn’t able to get a handle there, I think.
And so he moved to Bell Haps and worked on communication from a mathematical point of
view and was, you know, did all kinds of amazing work.
And so he’s just more on the signal side versus like the language side.
Yeah, it would have been interesting to see if you proceed the language side.
That’s really interesting.
He was interested in that.
His examples in the forties are kind of like, they’re very language-like things.
We can kind of show that there’s a noisy channel process going on in when you’re
listening to me, you know, you can often sort of guess what I meant by what I, you know,
what you think I meant given what I said.
And I mean, with respect to sort of why language looks the way it does, we might,
there might be sort of, as I alluded to, there might be ways in which word orders
is somewhat optimized for, because of the noisy channel in some way.
I mean, that’s really cool to sort of model if you don’t hear certain parts of a sentence
or have some probability of missing that part.
Like how do you construct a language that’s resilient to that?
That’s somewhat robust to that.
Yeah, that’s the idea.
And then you’re kind of saying like the word order and the syntax of the language,
the dependency length are all helpful.
Yeah.
Well, dependency length is really about memory.
I think that’s like about sort of what’s easier or harder to produce in some way.
And these other ideas are about sort of robustness to communication.
So the problem of potential loss of loss of signal due to noise.
And so that there might be aspects of word order, which is somewhat optimized for that.
And, you know, we have this one guest in that direction.
These are kind of just so stories.
I have to be, you know, pretty frank, they’re not like, I can’t show this is true.
All we can do is like, look at the current languages of the world.
This is like, we can’t sort of see how languages change or anything
because we’ve got these snapshots of a few, you know, 100 or a few thousand languages.
We don’t really, we can’t do the right kinds of modifications to test these things experimentally.
And so, you know, so just take this with a grain of salt, okay, from here, this stuff.
The dependency stuff, I can, I’m much more solid on.
I’m like, here’s what the lengths are, and here’s what’s hard, here’s what’s easy.
And this is a reasonable structure.
I think I’m pretty reasonable.
Here’s like, why, you know, why does a word order look the way it does?
Is we’re now into shaky territory, but it’s kind of cool.
But we’re talking about, just to be clear, we’re talking about maybe just actually the sounds of
communication, like you and I are sitting in the bar, it’s very loud.
And you model with a noisy channel, the loudness, the noise.
And we have the signal that’s coming across the, and you’re saying word order might have
something to do with optimizing that presence of noise.
It’s really interesting.
I mean, to me, it’s interesting how much you can load into the noisy channel,
like how much can you bake in?
You said like, you know, cognitive load on the receiver end.
We think that those are, there’s three, at least three different kinds of things going on there.
And we probably don’t want to treat them all as the same.
And so I think that you, you know, the right model, a better model of a noisy channel would
treat, would have three different sources of noise, which, because, which are background
noise, you know, speaker, speaker, um, inherent noise and listener inherent noise.
And those are not this, those are all different things.
Sure. But then underneath it, there’s a million other subsets.
Oh yeah. That’s true.
On the receiver, I mean, I just mentioned cognitive load on both sides.
Then there’s like, uh, speaking, uh, speech impediments or just everything.
World view, I mean, on the meeting, we start to creep into the meeting realm of like,
we have different world views.
Well, how about just form still though?
Like just, just what language do you know?
Like, so how well you know the language.
And so if it’s second language for you versus first language,
and in how, maybe what other languages you know, these are still just form stuff.
And that’s like potentially very informative.
And, and you know, how old you are, these things probably matter, right?
So like a child learning a language is, is a, you know, as a noisy representation of
English grammar, uh, you know, depending on how old they are.
So maybe when they’re six, they’re perfectly formed, but.
You mentioned one of the things is like a way to measure the, the, a language is learning problems.
So like, what’s the correlation between everything we’ve been talking about and
how easy it is to learn a language?
So is, is, uh, like, uh, short dependencies correlated to ability to learn a language?
Is there some kind of, or like the dependency grammars, there’s some kind of connection there?
How easy it is to learn?
Yeah. Well, all the languages in the world’s language, none is right now,
we know is any better than any other with respect to sort of optimizing dependency lengths,
for example, they’re all kind of do it, do it well.
They all keep low.
It’s, so the, I think of every human language is some kind of an opposite,
sort of an optimization problem, a complex optimization problem to this communication
problem. And so they’ve like, they’ve solved it, you know, they’re just sort of noisy solutions
to this problem of communication.
And there’s just so many ways you can do this.
So they’re not optimized for learning.
They’re probably less for communication.
And, and learning.
So yes, one of the factors, which is, yeah, so learning is messing this up a bit.
And so, so for example, if it were just about minimizing dependency lengths,
and that was all that matters, you know, then we, you know, so then,
then we might find grammars, which didn’t have regularity in their rules, like,
but languages always have regularity in their rules.
So, so what I mean by that is that if, if I wanted to say something to you in the,
in the optimal way to say it was, what really mattered to me, all that mattered was keeping
the dependencies as close together as possible, then I, then I would have a very lack set of
phrase structure or dependency rule that wouldn’t have very many of those.
I would have very little of that.
And I would just put the words as close to the things that refer to the things that
are connected right beside each other.
But we don’t do that.
Like there are, like there are word order rules, right?
So they’re very, and depending on the language, they’re more and less strict, right?
So you speak Russian, they’re less strict than English.
English is very rigid word order rules.
We order things in a very particular way.
And so why do we do that?
Like that’s probably not about communication.
That’s probably about learning.
I mean, then we’re talking about learning.
It’s probably easier to learn regular, regular things, things which are very predictable and
easy to, so that’s, that’s probably about learning is my, is our guess.
Cause that can’t be about communication.
Can it be just noise?
Can it be just the messiness of the development of a language?
Well, if it were just a communication, then we, we should have languages which have very,
very free word order.
And we don’t have that.
We have free err, but not free.
Like there’s always.
Well, no, but what I mean by noise is like cultural, like sticky cultural things,
like the way, the way you communicate, just there, there’s a stickiness to it.
That it’s, it’s an imperfect, it’s a noisy, it’s stochastic.
Yeah.
The, the, the function over which you’re optimizing is very noisy.
Yeah.
So, uh, because I don’t, it feels weird to say that learning is part of the objective
function because some languages are way harder to learn than others, right?
Or is that, that’s not true.
That’s interesting.
I mean, that’s the public perception, right?
Yes.
That’s true for a second language.
For a second language.
But that depends on what you started with, right?
So, so it’s, it really depends on how close that second language is to the first language
you’ve got.
And so yes, it’s very, very hard to learn Arabic if you’ve started with English or it’s
hard to, you know, hard to learn Japanese or if you’ve started with Chinese, I think
is the worst in the, there’s like Defense Language Institute in the United States has
like a list of, of, of how hard it is to learn what language from English.
I think Chinese is the worst.
But that’s just the second thing I see.
You’re saying babies don’t care.
No, no, there’s no evidence that there’s anything harder, easier about any baby,
any language learned, like by three or four, they speak that language.
And so there’s no evidence of any, anything harder, easier about any human language.
They’re all kind of equal.
To what degree is language, this is returning to Chomsky a little bit, is innate.
You said that for Chomsky, he used the idea that language is some aspect of language
are innate to explain away certain things that are observed.
But how much are we born with language at the core of our mind, brain?
I mean, I, you know, the answer is I don’t know, of course, but the, I mean, I, I like to,
I’m an engineer at heart, I guess.
And I sort of think it’s fine to postulate that a lot of it’s learned.
And so I, I’m guessing that a lot of it’s learned.
So I think the reason Chomsky went with the innateness
is because he, he hypothesized movement in his grammar.
He was interested in grammar and movement’s hard to learn.
I think he’s right.
Movement is a hard, it’s a hard thing to learn to learn these two things together
and how they interact.
And there’s like a lot of ways in which you might generate exactly the same sentences.
And it’s like really hard.
And so he’s like, Oh, I guess it’s learned.
So I guess it’s not learned, it’s innate.
And if you just throw out the movement and just think about that in a different way,
you know, then you, you get some messiness, but the messiness is human language,
which it’s actually fits better.
It’s that messiness isn’t a problem.
It’s actually a, it’s a valuable asset of, of, of the theory.
And so, so I think I don’t really see a reason to postulate much innate structure.
And that’s kind of, I think these large language models are learning so well
is because I think you can learn the form, the forms of human language from the input.
I think that’s like, it’s likely to be true.
So that part of the brain that lights up when you’re doing all the comprehension,
that could be learned.
That could be just, you don’t need, you don’t need to be innate.
So like lots of stuff is modular in the brain that’s learned.
It doesn’t have to, you know, so there’s something called the visual word form area
in the back.
And so it’s in the back of your head near the, you know, the visual cortex.
Okay.
And that is very specialized language, sorry, very specialized brain area,
which does visual word processing if you read, if you’re a reader.
Okay.
If you don’t read, you don’t have it.
Okay.
Guess what?
You spend some time learning to read and you develop that, that brain area,
which does exactly that.
And so these, the modularization is not evidence for innateness.
So the modularization of a language area doesn’t mean we’re born with it.
We could have easily learned that.
I, I, we might have been born with it.
I, I, we just, we just don’t know at this point.
We might very well have been born with this left lateralized area.
I mean that there’s like a lot of other interesting components here,
features of this kind of argument.
So some people get a stroke or something goes really wrong on the left side,
where the left, where language area would be, and that, and that isn’t there.
It’s not, not available.
And it develops just fine on the right.
And so it’s no lie.
So it’s not about the left.
It goes to the left.
Like this is a very interesting question.
It’s like, why is the, why are any of the brain areas the way that they are?
And how, how, how did they come to be that way?
And, you know, there’s these natural experiments, which happen where people
get these, you know, strange events in their brains at very young ages,
which wipe out sections of their brain and, and they behave totally normally.
And no one knows anything was wrong.
And we find out later, because they happened to be accidentally scanned for some reason.
And it’s like, what, what happened to your left hemisphere?
It’s missing.
There’s not many people who’ve missed their whole left hemisphere,
but they’ll be missing some other section of their left or their right.
And they behave absolutely normally, we’d never know.
So that’s like a very interesting, you know, current research.
You know, this is another project that this person and Federico is working on.
She’s got all these people contacting her because she’s scanned some people who have
been missing sections.
One person missing, missed a section of her brain and was scanned in her lab.
And, and she, and she happened to be a writer for the New York Times.
And there was an article in New York Times about, about the, just about the scanning
procedure and, and about what might be learned about by sort of the general process of MRI
and language and that’s her language.
And, and because she’s writing for the New York Times,
then all these people started writing to her who also have similar,
similar kinds of deficits because they’ve been, you know, accidentally,
you know, to scan for some reason and, and found out they’re missing some section.
And they, they volunteer to be scanned.
These are natural experiments.
Natural experiments.
They’re kind of messy, but natural experiments, kind of cool.
She calls them interesting brains.
The first few hours, days, months of human life are fascinating.
It’s like, well, inside the womb actually, like that development,
that machinery, whatever that is, seems to create powerful humans that are able to
speak, comprehend, think all that kind of stuff, no matter what happened,
not no matter what, but robust to the different ways that the brain might be damaged and so on.
That’s, that’s really, that’s really interesting.
But what would Chomsky say about the fact, the thing you’re saying now that language
is, is, seems to be happening separate from thought, because as far as I understand,
maybe you can correct me, he thought that language underpins.
Yeah, he thinks so.
I don’t know what he’d say.
He would be surprised because for him, the idea is that language
is the sort of the foundation of thought.
That’s right.
Absolutely.
And it’s pretty mind blowing to think that it could be completely separate from thought.
That’s right.
But so, you know, he’s basically a philosopher, philosopher of language in a way,
thinking about these things.
It’s a fine thought.
You can’t test it in his methods.
You can’t do a thought experiment to figure that out.
You need a scanner.
You need brain damage people.
You need something.
You need ways to measure that.
And that’s what, you know, fMRI offers as a, and, and, you know, patients are a little messier.
fMRI is pretty unambiguous, I’d say.
It’s like very unambiguous.
There’s no way to say that the language network is doing any of these tasks.
There’s, like, you should look at those data.
It’s like there’s no chance that you can say that those networks are overlapping.
They’re not overlapping.
They’re just like completely different.
And so, you know, so, you know, you can always make, you know, it’s only two people.
It’s four people or something for the patients.
And there’s something special about them we don’t know.
But these are just random people and with lots of them, and you find always the same effects.
And it’s very robust, I’d say.
What’s the fascinating effect?
What’s the, you mentioned Bolivia.
What’s the connection between culture and language?
You’ve, you’ve also mentioned that, you know, much of our study of language comes from
WEIRD, Weird People, Western Educated Industrialized Rich and Democratic.
So when you study, like, remote cultures such as around the Amazon jungle,
what can you learn about language?
So that term WEIRD is from Joe Henrich.
He’s at Harvard.
He’s a Harvard evolutionary biologist.
And so he works on lots of different topics.
And he basically was pushing that observation that we should be careful about the inferences
we want to make when we’re talking in psychology or social, yeah, mostly in psychology, I guess,
about humans if we’re talking about, you know, undergrads at MIT and Harvard.
Those aren’t the same, right?
These aren’t the same things.
And so if you want to make inferences about language, for instance, you,
there’s a lot of very, a lot of other kinds of languages in the world, then English and French
and Chinese, you know, and so maybe for language, we care about how culture, because cultures can be
very, I mean, of course, English and Chinese cultures are very different, but, you know,
hunter-gatherers are much more different in some ways.
And so, you know, if culture hasn’t affected what language is, then we kind of want to look
there as well as looking, it’s not like the industrialized cultures aren’t interesting,
of course they are, but we want to look at non-industrialized cultures as well.
And so I worked with two, I worked with the Chimani, which are in Bolivia and in the Amazon,
both in the Amazon, in these cases.
And there are so-called farmer foragers, which is not hunter-gatherers.
It’s sort of one up from hunter-gatherers in that they do a little bit of farming as well,
a lot of hunting as well, but a little bit of farming.
And the kind of farming they do is the kind of farming that I might do.
If I ever were to grow like tomatoes or something in my backyard, it’s not like,
so it’s not like big field farming, it’s just a farming for a family,
a few things you do that.
And so that’s what, that’s the kind of farming they do.
And the other group I’ve worked with are the Pirajá, which are in, also in the Amazon,
and happen to be in Brazil.
And that’s with a guy called Dan Everett, who is a linguist anthropologist who actually lived
and worked in the, I mean, he was a missionary actually, initially, back in the 70s,
working with, trying to translate languages so they could teach them the Bible,
teach them Christianity.
What can you say about that?
Yeah, so the two groups I’ve worked with, the Cimani and the Pirajá, are both
Isolate languages, meaning there’s no known connected languages at all.
They’re just like on their own.
Oh, cool.
Yeah, there’s a lot of those.
And most of the Isolates occur in the Amazon or in Papua New Guinea,
in these places where the world has sort of stayed still for long enough.
And they’re, like, so there aren’t earthquakes.
There aren’t, well, certainly no earthquakes in the Amazon jungle.
And the climate isn’t bad, so you don’t have droughts.
And so, you know, in Africa, you’ve got a lot of moving of people because there’s
drought problems.
And so they get a lot of language contact when you have, when people have to,
if you’ve got to move because you’ve got no water, then you’ve got to get going.
And then you run into contact with other tribes, other groups.
In the Amazon, that’s not the case.
And so people can stay there for hundreds and hundreds and probably thousands
of years, I guess.
And so these groups have, the Cimani and the Pirajá are both Isolates in that.
And they just, I guess they’ve just lived there for ages and ages with minimal
contact with other outside groups.
And so, I mean, I’m interested in them because they are, I mean, I, you know,
in these cases, I’m interested in their words.
So I would love to study their syntax, their orders of words, but I’m mostly just
interested in how languages, you know, are connected to their cultures in this way.
And so with the Pirajá, the most interesting, I was working on number
there, number information.
And so the basic idea is I think language is invented.
That’s what I get from the words here, is that I think language is invented.
We talked about color earlier.
It’s the same idea.
So that what you need to talk about with someone else is what you’re going to
invent words for.
Okay.
And so we invent labels for colors that I need, not that I can see, but that things
I need to tell you about so that I can get objects from you or get you to give
me the right objects.
And I just don’t need a word for teal or a word for aquamarine in the Amazon jungle,
for the most part, because I don’t have two things which differ on those colors.
I just don’t have that.
And so numbers are really another fascinating source of information here where
you might, you know, naively, I certainly thought that all humans would have words
for exact counting and the Pirajá don’t.
Okay.
So they don’t have any words for even one.
There’s not a word for one in their language.
And so there’s certainly not a word for two, three or four.
So that kind of blows people’s minds off.
Yeah, that’s blowing my mind.
That’s pretty weird.
How are you going to ask, I want two of those?
You just don’t.
And so that’s just not a thing you can possibly ask in the Pirajá.
It’s not possible.
That is, there’s no words for that.
So here’s how we found this out.
Okay.
So it was thought to be a one, two, many language.
There are three words, four quantifiers for sets.
But people had thought that those meant one, two and many.
But what they really mean is few, some and many.
Many is correct.
It’s few, some and many.
And so the way we figured this out, and this is kind of cool,
is that we gave people, we had a set of objects.
Okay.
And these were having to be spools of thread.
It doesn’t really matter what they are.
Identical objects.
And when I sort of start off here, I just give, you know,
give you one of those and say, what’s that?
Okay.
I see you’re a Peter Hall speaker and you tell me what it is.
And then I give you two and say, what’s that?
And nothing’s changing in this set except for the number.
Okay.
And then I just ask you to label these things.
We just do this for a bunch of different people.
And frankly, I did this task.
This is fascinating.
And it’s a little bit weird.
So they say the word that we thought was one, it’s few,
but for the first one.
And then maybe they say few or maybe they say some for the second.
And then for the third or the fourth,
they start using the word many for the set.
And then five, six, seven, eight.
I go all the way to 10.
And it’s always the same word.
And they look at me like I’m stupid because they told me
what the word was for six, seven, eight.
And I’m going to continue asking them at nine and 10.
I’m sorry.
I just, I just, they understand that I want to know their language.
That’s the point of the task is like I’m trying to learn their language.
And so that’s okay.
But it does seem like I’m a little slow because I,
they already told me what the word for many was five, six, seven.
And I keep asking.
So it’s a little funny to do this task over and over.
We did this with the guy called Dan was the translator.
He’s the only one who really speaks Piraha fluently.
He’s a good bilingual for a bunch of languages, but also English and Piraha.
And then a guy called Mike Frank was also a student with me down there.
He and I did these things.
And so you do that.
Okay.
And everyone does the same thing.
They all, all, all, you know, we asked like 10 people and they all do
exactly the same labeling for one up.
And then we just do the same thing down on like random order.
Actually, we do some of them up, some of them down first.
Okay.
And so we do, instead of one to 10, we do 10 down to one.
And so, so I give them 10, nine and eight.
They start saying the word for some.
And then at down to, when you get to four, everyone is saying the word for few,
which we thought was one.
So it’s like, it’s the context determined what word, what, what,
what that quantifier they used was.
So it’s not a count word.
They’re not, they’re not count words.
They’re, they’re just approximate words.
And they’re going to be noisy when you interview a bunch of people,
the, what the definition of few, and there’s going to be a threshold in the context.
Yeah.
Yeah.
I don’t know what that means.
That’s, that’s going to be 10 on the context.
I think it’s true in English too, right?
If you ask an English person, what a few is.
I mean, that’s dependent completely on the context.
And it might actually be at first hard to discover.
Yeah.
Because for a lot of people, the jump from one to two will be few.
Right.
So it’s a jump.
Yeah.
It might be, it might still be there.
Yeah.
Right.
It’s, I mean, that’s fascinating.
That’s fascinating that numbers don’t present themselves.
Yeah.
So the words aren’t there.
And then, and so then we do these other things.
Well, if, if they don’t have the words, can they do exact matching kinds of tasks?
Can they even do those tasks?
And, and, and the answer is sort of yes and no.
And so yes, they can do them.
So here’s the tasks that we did.
We put out those spools of thread again.
Okay.
So maybe I put like three out here.
And then we gave them some objects.
And those happen to be uninflated red balloons.
It doesn’t really matter what they are.
It’s just a bunch of exactly the same thing.
And it was easy to put down right next to these spools of thread.
Okay.
And so then I put out three of these.
And your task was to just put one against each of my three things.
And they can do that perfectly.
So I mean, I would actually do that.
It was a very easy task to explain to them because I have,
I did this with this guy, Mike Frank.
And he would be my, I’d be the experimenter telling him to do this
and showing him to do this.
And then we just like, just do what he did.
You’ll copy him.
All we had to, I didn’t have to speak Peter Ha, except for know what, copy him.
Like do what he did is like all we had to be able to say.
And then they would do that just perfectly.
And so we’d move it up.
We’d do some sort of random number of items up to 10.
And they basically do perfectly on that.
They never get that wrong.
I mean, that’s not a counting task, right?
That is just a match.
You just put one against that.
It doesn’t matter how many,
I don’t need to know how many there are there to do that correctly.
And, and they would make mistakes, but very, very few and no more than MIT undergrads.
Just going to say, like there’s no, these are low stakes.
So, you know, you make mistakes.
So counting is not required to complete the matching task.
That’s right.
Not at all.
Okay.
And so, and so that’s our control.
And this guy had gone down there before and said that they couldn’t do this task,
but I just don’t know what he did wrong there because they can do this task perfectly well.
And, you know, I can, can train my dog to do this task.
So of course they can do this task.
And so, you know, it’s not a hard task.
But the other task that was sort of more interesting is like,
so then we do a bunch of tasks where you need some way to encode the set.
So like one of them is just, I just put a opaque sheet in front of the things.
I put down a bunch, a set of these things, and I put an opaque sheet down.
And so you can’t see them anymore.
And I tell you, do the same thing you were doing before, right?
You know, and it’s easy if it’s two or three, it’s very easy.
But if I don’t have the words for eight, it’s a little harder.
Like maybe, you know, with practice went, well, no.
Because you have to count.
For us, it’s easy because we just, we just count them.
It’s just so easy to count them.
But they don’t, they can’t count them because they don’t count.
They don’t have words for this thing.
And so they would do approximate.
It’s totally fascinating.
So they would get them approximately right, you know, after four or five.
You know, because you can basically always get four right, three or four.
That looks, that’s something we can visually see.
But after that, you kind of have, it’s an approximate number.
And so then, and there’s a bunch of tasks we did and they all failed as, I mean, failed.
They did approximate after five on all those tasks.
And it kind of shows that the words, you kind of need the words, you know,
to be able to do these kinds of tasks.
Because there’s a little bit of a chicken and egg thing there.
Because if you don’t have the words, then maybe they’ll limit you in the kind of,
like a little baby Einstein there, won’t be able to come up with a counting task.
You know what I mean?
Like the ability to count enables you to come up with interesting things probably.
So yes, you develop counting because you need it.
But then once you have counting, you can probably come up with a bunch of different inventions.
Like how to, I don’t know, what kind of thing they do matching really well for building purposes,
building some kind of hut or something like this.
So it’s interesting that language is a limiter on what you’re able to do.
Yeah, here’s language is just, is the words.
Here is the words.
Like the words for exact count is the limiting factor here.
They just don’t have them.
Yeah, that’s what I mean.
That limit is also a limit on the society of what they’re able to build.
That’s going to be true.
Yeah.
So it’s probable.
I mean, we don’t know, this is one of those problems with the snapshot of just current languages,
is that we don’t know what causes a culture to discover/invent a counting system.
But the hypothesis is the guess out there is something to do with farming.
So if you have a bunch of goats and you want to keep track of them,
and you save 17 goats and you go to bed at night and you get up in the morning,
boy, it’s easier to have a count system to do that.
You know, that’s an abstraction over a set.
So that I don’t have, like people often ask me when I talk to them about this kind of work,
they say, “Well, don’t these children have kids?
Don’t they have a lot of children?”
I’m like, “Yeah, they have a lot of children.”
And they do.
They often have families of three or four or five kids.
And they go, “Well, don’t they need the numbers to keep track of their kids?”
And I always ask the person who says this, like, “Do you have children?”
And the answer is always, “No.”
Because that’s not how you keep track of your kids.
You care about their identities.
It’s very important to me when I go, “I think I have five children.”
It doesn’t matter which, it matters which five.
It’s like, if you replaced one with someone else, I would care.
Goat maybe not, right?
That’s the kind of point.
It’s an abstraction.
Something that looks very similar to the one wouldn’t matter to me, probably.
But if you care about goats, you’re going to know them actually individually also.
Yeah, you will.
I mean, cows and goats, if there’s a source of food and milk and all that kind of stuff,
you’re going to actually really do the care.
But I’m saying it is an abstraction such that you don’t have to care
about their identities to do this thing fast.
That’s the hypothesis, not mine.
From anthropologists are guessing about where words for counting came from,
is from farming maybe.
Yeah. Do you have a sense why universal languages like Esperanto have not taken off?
Like why do we have all these different languages?
Well, my guess is that the function of a language is to do something in a community.
I mean, unless there’s some function to that language in the community,
it’s not going to survive.
It’s not going to be useful.
So here’s a great example.
Language death is super common.
Languages are dying all around the world.
And here’s why they’re dying.
And it’s like, yeah, I see this in, you know, it’s not happening right now
in either the Chimane or the Piedoha, but it probably will.
And so there’s a neighboring group called Mosetan, which is, I said that it’s an isolates.
Actually, there’s a dual.
There’s two of them.
Okay. So it’s actually, there’s two languages, which are really close,
which are Mosetan and Chimane, which are unrelated to anything else.
And Mosetan is unlike Chimane in that it has a lot of contact with Spanish and it’s dying.
So that language is dying.
The reason it’s dying is there’s not a lot of value for the local people in their native language.
So there’s much more value in knowing Spanish like because they want to feed their families.
And how do you feed your family?
You learn Spanish so you can make money so you can get a job and do these things.
And then you can, and then you make money.
And so they want Spanish things, they want, and so Mosetan is in danger and is dying.
And that’s normal.
And so basically the problem is that people, the reason we learn languages to communicate,
and we need to, we use it to make money and to do whatever it is to feed our families.
And if that’s not happening, then it won’t take off.
It’s not like a game or something.
This is like something we use.
Like, why is English so popular?
It’s not because it’s an easy language to learn.
Maybe it is.
I don’t really know.
But that’s not why it’s popular.
But because the United States is a gigantic economy and therefore…
It’s big economies that do this.
It’s all it is.
It’s all about money and that’s what…
And so there’s a motivation to learn Mandarin.
There’s a motivation to learn Spanish.
There’s a motivation to learn English.
These languages are very valuable to know because there’s so, so many speakers all over the world.
That’s fascinating.
There’s less of a value economically.
It’s like kind of what drives this.
It’s not just for fun.
I mean, there are these groups that do want to learn language just for language’s sake.
And then there’s something to that.
But those are rare.
Those are rarities in general.
Those are a few small groups that do that.
Not most people don’t do that.
Well, if that was the primary driver, then everybody was speaking English or speaking one language.
There’s also attention.
That’s happening.
And that, well…
We’re moving towards fewer and fewer languages.
We are.
I wonder if…
You’re right.
Maybe this is slow, but maybe that’s where we’re moving.
But there is attention.
You’re saying a language that defringes.
But if you look at geopolitics and superpowers, it does seem that there’s another thing of
tension, which is a language is a national identity sometimes.
For certain nations.
I mean, that’s the war in Ukraine.
Language, Ukrainian language is a symbol of that war in many ways.
Like a country fighting for its own identity.
So it’s not merely the convenience.
I mean, those two things that are attention is the convenience of trade and the economics
and be able to communicate with neighboring countries and trade more efficiently with
neighboring countries, all that kind of stuff, but also identity of the group.
That’s right.
I completely agree.
This language is the way…
For every community, like dialects that emerge are a kind of identity for people.
Sometimes a way for people to say F-U to the more powerful people.
That’s interesting.
So in that way, language can’t be used as that tool.
I completely agree.
And there’s a lot of work to try to create that identity.
So people want to do that speak as a cognitive scientist and language expert.
I hope that continues because I don’t want languages to die.
I want languages to survive because they’re so interesting for so many reasons.
But I mean, I find them fascinating just for the language part.
But I think there’s a lot of connections to culture as well, which is also very important.
Do you have hope for machine translation that can break down the barriers of language?
So while all these different diverse languages exist, I guess there’s many ways of asking
this question, but basically how hard is it to translate in an automated way for one language
to another?
There’s going to be cases where it’s going to be really hard.
So there are concepts that are in one language and not in another.
Like the most extreme kinds of cases are these cases of number information.
So good luck translating a lot of English into Piraha.
It’s just impossible.
There’s no way to do it because there are no words for these concepts that we’re talking about.
There’s probably the flip side, right?
There’s probably stuff in Piraha, which is going to be hard to translate into English
on the other side.
And so I just don’t know what those concepts are.
I mean, the space, the world space is different from my world space.
And so I don’t know what, so that the things they talk about, things are,
it’s going to have to do with their life as opposed to my industrial life,
which is going to be different.
And so there’s going to be problems like that always.
There’s like, maybe it’s not so bad in the case of some of these spaces,
and maybe it’s going to be harder than others.
And so it’s pretty bad in number.
It’s like extreme, I’d say, in the number space, exact number space.
But in the color dimension, right?
So that’s not so bad.
I mean, but it’s a problem that you don’t have ways to talk about the concepts.
And there might be entire concepts that are missing.
So to you, it’s more about the space of concept versus the space of form.
Like form, you can probably map.
Yes.
Yeah. But so you were talking earlier about translation
and about how translations, there’s good and bad translations.
I mean, now you’re talking about translations of form, right?
So what makes writing good, right?
There’s a music to the form.
Right. It’s not just the content.
It’s how it’s written.
And translating that, that sounds difficult.
We should say that there is like, I don’t hesitate to say meaning,
but there’s a music and a rhythm to the form.
When you look at the broad picture, like the Fritz Wietzi and Dostoyevsky and Tolstoy,
or Hemingway Bukowski, James Joyce, like I mentioned, there’s a beat to it.
There’s an edge to it that’s like, is in the form.
We can probably get measures of those.
Yeah.
I don’t know.
I’m optimistic that we could get measures of those things.
And so maybe that’s…
Translatable.
I don’t know. I don’t know, though.
I have not worked on that.
I would love to see…
That sounds totally fascinating.
Translation to Hemingway is probably the lowest…
I would love to see different authors,
but the average per sentence dependency length for Hemingway is probably the shortest.
That’s your sense, huh?
It’s simple sentences.
Simple sentences.
Short, yeah, yeah, yeah, yeah.
I mean, that’s when, if you have really long sentences,
even if they don’t have center, like…
They can have longer connections.
They can have longer connections.
They don’t have to, right?
You can’t have a long, long sentence with a bunch of local words, yeah.
But it is much more likely to have the possibility
of long dependencies with long sentences, yeah.
I met a guy named Azar Askin who does a lot of cool stuff.
Really brilliant.
Works with Tristan Harris and a bunch of stuff.
But he was talking to me about communicating with animals.
He co-founded Earth Species Project,
where you’re trying to find the common language between whales, crows, and humans.
And he was saying that there’s a lot of promising work,
that even though the signals are very different,
like the actual, if you have embeddings of the languages,
they’re actually trying to communicate similar type things.
Is there something you can comment on that?
Where is there a promise to that?
In everything you’ve seen in different cultures,
especially like remote cultures, that this is a possibility?
Or no?
Like we can talk to whales?
I would say yes.
I think it’s not crazy at all.
I think it’s quite reasonable.
But there’s this sort of weird view, well, odd view,
I think, that to think that human language is somehow special.
I mean, it is, maybe it is.
We can certainly do more than any of the other species.
You know, and maybe our language system is part of that.
It’s possible.
But people have often talked about how human, like Chomsky, in fact,
has talked about how human language has this compositionality thing
that he thinks is sort of key in language.
And the problem with that argument is he doesn’t speak whale.
And he doesn’t speak crow, and he doesn’t speak monkey.
You know, he’s like, they say things like,
well, they’re making a bunch of grunts and squeaks.
And the reasoning is like, that’s bad reasoning.
Like, you know, I’m pretty sure if you asked a whale what we’re saying,
they’d say, well, I’m making a bunch of weird noises.
Exactly.
And so it’s like, this is a very odd reasoning to be making,
that human language is special because we’re the only one
to have human language.
I’m like, well, we don’t know what those other, we just don’t,
we can’t talk to them yet.
And so there are probably a signal in there.
And it might very well be something complicated like human language.
I mean, sure, with a small brain, in lower species,
there’s probably not a very good communication system.
But in these higher species where you have, you know,
what seems to be, you know, abilities to communicate something,
there might very well be a lot more signal there than we might have otherwise thought.
But also, if we have a lot of intellectual humility here,
there’s somebody formerly from MIT, Neri Oxman,
who I admire very much, has talked a lot about,
has worked on communicating with plants.
So like, yes, the signal there is even less than,
but like, it’s not out of the realm of possibility
that all nature has a way of communicating.
And it’s a very different language,
but they do develop a kind of language through the chemistry,
through some way of communicating with each other.
And if you have enough humility about that possibility,
I think you can, I think it would be a very interesting,
in a few decades, maybe centuries, hopefully not,
a humbling possibility of being able to communicate,
not just between humans, effectively,
but between all of living things on Earth.
Well, I mean, I think some of them are not going to have much interesting to say.
But you could still.
We don’t know.
We certainly don’t know, I think.
I think if we were humble,
there could be some interesting trees out there.
Well, they’re probably talking to other trees, right?
They’re not talking to us.
And so to the extent they’re talking,
they’re saying something interesting to some other,
you know, conspecific as opposed to us, right?
And so they probably is, there may be some signal there.
So there are people out there,
actually it’s pretty common to say that human language is special
and different from any other animal communication system.
And I just don’t think the evidence is there for that claim.
I think it’s not obvious.
We just don’t know what,
because we don’t speak these other communication systems
until we get better.
You know, I do think there are people working on that,
as you pointed out, though,
people working on whale speak, for instance.
Like, that’s really fascinating.
Let me ask you a wild out there sci-fi question.
If we make contact with an intelligent alien civilization,
and you get to meet them, how hard do you think you,
like how surprised would you be about their way of communicating?
Do you think it would be recognizable?
Maybe there’s some parallels here when you go to the remote drives.
I mean, I would want Dan Everett with me.
He is like amazing at learning foreign languages.
And so he like, this is an amazing feat, right?
To be able to go.
This is a language, which has no translators before him.
I mean, there were, he was a missionary.
Well, there was a guy that had been there before,
but he wasn’t very good.
And so he learned the language far better
than anyone else had learned before him.
He’s like good at, he’s just a, he’s a very social person.
I think that’s a big part of it, is being able to interact.
So I don’t know, it kind of depends on these,
these, the species from outer space,
how much they want to talk to us.
Is there something you can say about the process he follows?
Like what, how do you show up to a tribe and socialize?
I mean, I guess colors and counting
is one of the most basic things to figure out.
Yeah, you start that.
You actually start with like objects and just say,
you know, just throw a stick down and say stick.
And then you say, what do you call this?
And then they’ll say the word, whatever.
And he says a standard thing to do is to throw two sticks at two sticks.
And then, you know, he learned pretty quick
that there weren’t any count words in this language
because they didn’t know this wasn’t interesting to them.
It was kind of weird.
They’d say some or something in the same word over and over again.
And so, but that is a standard thing.
You just like try to,
but you have to be pretty out there socially,
like willing to talk to random people.
Which these are, you know, really very different people from you.
And he was, and he’s very social.
And so I think that’s a big part of this is like, that’s how,
you know, a lot of people know a lot of languages
that they’re willing to talk to other people.
That’s a tough one.
We just show up knowing nothing.
Yeah. Oh, God.
That’s beautiful.
It’s beautiful that humans are able to connect in that way.
Yeah. Yeah.
You’ve had an incredible career exploring this fascinating topic.
What advice would you give to young people
about how to have a career?
Like that or a life that they can be proud of?
When you see something interesting, just go and do it.
Like I do, I do that.
Like that’s something I do,
which is kind of unusual for most people.
So like when I saw the Piroja,
like if Piroja was available to go and visit,
I was like, yes, yes, I’ll go.
And then when we couldn’t go back,
we had some trouble with the Brazilian government.
There’s some corrupt people there.
It was very difficult to get, go back in there.
And so I was like, all right, I got to find another group.
And so we searched around and we were able to find the,
because I wanted to keep working on this kind of problem.
And so we found the Chamani and just go there.
I didn’t really have, we didn’t have contact.
We had a little bit of contact and brought someone.
And that was, you know, we just kind of just try things.
I say it’s like, a lot of that just like ambition,
just try to do something that other people haven’t done.
Just give it a shot is what I, I mean, I do that all the time.
I don’t know.
I love it.
And I love the fact that your pursuit of fun
has landed you here talking to me.
This was an incredible conversation
that you’re, you’re, you’re just a fascinating human being.
Thank you for taking a journey
through human language with me today.
This is awesome.
Thank you very much.
Lex has been pleasure.
Thanks for listening to this conversation
with Edward Gibson to support this podcast.
Please check out our sponsors in the description.
And now let me leave you with some words from Wittgenstein.
The limits of my language mean the limits of my world.
Thank you for listening and hope to see you next time.
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[MUSIC]

Edward Gibson is a psycholinguistics professor at MIT and heads the MIT Language Lab. Please support this podcast by checking out our sponsors:
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Transcript: https://lexfridman.com/edward-gibson-transcript

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OUTLINE:
Here’s the timestamps for the episode. On some podcast players you should be able to click the timestamp to jump to that time.
(00:00) – Introduction
(10:53) – Human language
(14:59) – Generalizations in language
(20:46) – Dependency grammar
(30:45) – Morphology
(39:20) – Evolution of languages
(42:40) – Noam Chomsky
(1:26:46) – Thinking and language
(1:40:16) – LLMs
(1:53:14) – Center embedding
(2:19:42) – Learning a new language
(2:23:34) – Nature vs nurture
(2:30:10) – Culture and language
(2:44:38) – Universal language
(2:49:01) – Language translation
(2:52:16) – Animal communication

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