The following is a conversation with Noam Chomsky.
He's truly one of the great minds of our time
and is one of the most cited scholars
in the history of our civilization.
He has spent over 60 years at MIT
and recently also joined the University of Arizona
where we met for this conversation.
But it was at MIT about four and a half years ago
when I first met Noam.
In my first few days there,
I remember getting into an elevator at Stata Center,
pressing the button for whatever floor,
looking up and realizing it was just me and Noam Chomsky
riding the elevator.
Just me and one of the seminal figures of linguistics,
cognitive science, philosophy and political thought
in the past century, if not ever.
I tell that silly story because I think life is made up
of funny little defining moments that you never forget
for reasons that may be too poetic to try and explain.
That was one of mine.
Noam has been an inspiration to me
and millions of others.
It was truly an honor for me
to sit down with him in Arizona.
I traveled there just for this conversation
and in a rare heartbreaking moment
after everything was set up and tested,
the camera was moved and accidentally
the recording button was pressed,
stopping the recording.
So I have good audio of both of us, but no video of Noam.
Just the video of me and my sleep deprived
but excited face that I get to keep
as a reminder of my failures.
Most people just listen to this audio version
for the podcast as opposed to watching it on YouTube.
But still, it's heartbreaking for me.
I hope you understand
and still enjoy this conversation as much as I did.
The depth of intellect that Noam showed
and his willingness to truly listen to me,
a silly looking Russian in a suit.
It was humbling and something I'm deeply grateful for.
As some of you know, this podcast is a side project for me
where my main journey and dream is to build AI systems
that do some good for the world.
This latter effort takes up most of my time
but for the moment has been mostly private.
But the former, the podcast is something
I put my heart and soul into.
And I hope you feel that even when they screw things up.
I recently started doing ads at the end of the introduction.
I'll do one or two minutes after introducing the episode
and never any ads in the middle
that break the flow of the conversation.
I hope that works for you.
It doesn't hurt the listening experience.
This is the Artificial Intelligence Podcast.
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Alex Friedman spelled F-R-I-D-M-A-N.
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And now, here's my conversation with Noam Chomsky.
I apologize for the absurd philosophical question,
but if an alien species were to visit Earth,
do you think we would be able to find a common language
or protocol of communication with them?
There are arguments to the effect that we could.
In fact, one of them was Marvin Minsky's.
Back about 20 or 30 years ago,
he performed a brief experiment
with a student of his, Dan Bobrow.
They essentially ran the simplest possible touring machines,
just for you to see what would happen.
And most of them crashed,
either got into an infinite loop or stopped.
The few that persisted essentially gave something like arithmetic.
And his conclusion from that was
that if some alien species developed higher intelligence,
they would at least have arithmetic.
They would at least have what the simplest computer would do.
And in fact, he didn't know that at the time,
but the core principles of natural language
are based on operations,
which yield something like arithmetic
in the limiting case and the minimal case.
So it's conceivable that a mode of communication
could be established based on the core properties
of human language and the core properties of arithmetic,
which maybe are universally shared.
So it's conceivable.
What is the structure of that language,
of language as an internal system inside our mind
versus an external system as it's expressed?
It's not an alternative.
It's two different concepts of language.
Different.
It's a simple fact that there's something about you,
a trait of yours, part of the organism,
you that determines that you're talking English
and not Tagalog, let's say.
So there is an inner system.
It determines the sound and meaning
of the infinite number of expressions of your language.
It's localized.
It's not in your foot, obviously.
It's in your brain.
If you look more closely,
it's in specific configurations of your brain.
And that's essentially like the internal structure
of your laptop, whatever programs it has are in there.
Now, one of the things you can do with language,
it's a marginal thing, in fact,
is use it to externalize what's in your head.
Actually, most of your use of language
is thought, internal thought,
but you can do what you and I are now doing.
We can externalize it.
Well, the set of things that we're externalizing
are an external system.
They're noises in the atmosphere.
And you can call that language
in some other sense of the word,
but it's not a set of alternatives.
These are just different concepts.
So how deep do the roots of language go in our brain?
Our mind, is it yet another feature like vision
or is it something more fundamental
from which everything else springs in the human mind?
Well, in a way, it's like vision.
There's something about our genetic endowment
that determines that we have a mammalian
rather than an insect visual system.
And there's something in our genetic endowment
that determines that we have a human language faculty.
No other organism has anything remotely similar.
So in that sense, it's internal.
Now, there is a long tradition,
which I think is valid going back centuries
to the early scientific revolution,
at least, that holds that language
is the core of human cognitive nature.
It's the source.
It's the mode for constructing thoughts
and expressing them.
That is what forms thought.
And it's got fundamental creative capacities.
It's free, independent, unbounded, and so on.
And undoubtedly, I think the basis
for our creative capacities
and the other remarkable human capacities
that lead to the unique achievements
and not so great achievements of the species.
The capacity to think and reason,
do you think that's deeply linked with language?
Do you think the way the internal language system
is essentially the mechanism
by which we also reason internally?
It is undoubtedly the mechanism by which we reason.
There may also be other fact,
there are undoubtedly other faculties involved in reasoning.
We have a kind of scientific faculty.
Nobody knows what it is,
but whatever it is that enables us to pursue
a certain lines of endeavor and inquiry
and to decide what makes sense and doesn't make sense
and to achieve a certain degree
of understanding of the world,
that uses language but goes beyond it.
Just as using our capacity for arithmetic
is not the same as having the capacity.
The idea of capacity, our biology, evolution,
you've talked about it defining essentially our capacity,
our limit and our scope.
Can you try to define what limit and scope are
and the bigger question,
do you think it's possible to find the limit
of human cognition?
Well, that's an interesting question.
It's commonly believed, most scientists believe
that a human intelligence can answer any question
in principle.
I think that's a very strange belief.
If we're biological organisms, which are not angels,
then our capacities ought to have scope and limits,
which are interrelated.
Can you define those two terms?
Well, let's take a concrete example.
Your genetic endowment determines
that you can have a male in visual system,
arms and legs and so on.
But it, and therefore become a rich complex organism.
But if you look at that same genetic endowment,
it prevents you from developing in other directions.
There's no kind of experience which would yield
the embryo to develop an insect visual system
or to develop wings instead of arms.
So the very endowment that confers richness and complexity
also sets bounds on what can be attained.
Now, I assume that our cognitive capacities
are part of the organic world.
Therefore, they should have the same properties.
If they had no built-in capacity
to develop a rich and complex structure,
we would have understand nothing.
Just as if your genetic endowment
did not compel you to develop arms and legs,
you would just be some kind of a random amoeboid creature
with no structure at all.
So I think it's plausible to assume that there are limits.
And I think we even have some evidence as to what they are.
So for example, there's a classic moment
in the history of science at the time of Newton.
There was a, from Galileo to Newton, modern science,
developed on a fundamental assumption,
which Newton also accepted,
namely that the world is, the entire universe,
is a mechanical object.
And by mechanical, they meant something like
the kinds of artifacts that were being developed
by skilled artisans all over Europe,
the gears, the levers, and so on.
And their belief was, well, the world
is just a more complex variant of this.
Newton, to his astonishment and distress,
proved that there are no machines,
that there's interaction without contact.
His contemporaries like Leibniz and Huygens
just dismissed this as returning
to the mysticism of the neoscholastics.
And Newton agreed.
He said, it is totally absurd.
No person of any scientific intelligence
could ever accept this for a moment.
In fact, he spent the rest of his life
trying to get around it somehow,
as did many other scientists.
That was the very criterion of intelligibility
for, say, Galileo or Newton theory
did not produce an intelligible world
unless you get duplicated in a machine.
He said, you can't, there are no machines.
And he finally, after a long struggle, took a long time,
scientists just accepted this as common sense.
But that's a significant moment.
That means they abandoned the search
for an intelligible world.
And the great philosophers of the time
understood that very well.
So for example, David Hume, in his encomium to Newton,
wrote that, who was the greatest thinker ever and so on,
he said that he unveiled many of the secrets of nature,
but by showing the imperfections
of the mechanical philosophy, mechanical science,
he left us with, he showed that there are mysteries
which ever will remain.
And science just changed its goals.
It abandoned the mystery, said,
can't solve it, we'll put it aside.
We only look for intelligible theories.
Newton's theories were intelligible.
It's just what they described wasn't.
Well, what, Locke said the same thing.
I think they're basically right.
And if so, that should,
something about the limits of human cognition.
We cannot attain the goal of understanding the world,
of finding an intelligible world.
This mechanical philosophy, Galileo to Newton,
this good case can be made
that that's our instinctive conception of how things work.
So if say infants are tested with things that,
if this moves and then this moves,
they kind of invent something that must be invisible,
that's in between them, that's making the move and so on.
Yeah, we like physical contact.
Something about our brain seeks.
Makes us want a world like that,
just like it wants a world that has regular geometric figures.
So for example, Descartes pointed this out,
that if you have an infant who's never seen a triangle before
and you draw a triangle,
the infant will see a distorted triangle,
not whatever crazy figure it actually is.
You know, three lines not coming quite together,
one of them a little bit curved and so on.
We just impose a conception of the world
in terms of geometric, perfect geometric objects.
It's now been shown that goes way beyond that,
that if you show on a tachistoscope,
let's say a couple of lights shining,
you do it three or four times in a row,
what people actually see is a rigid object in motion,
not whatever's there.
But we all know that from a television set, basically.
So that gives us hints of potential limits to our cognition.
I think it does, but it's a very contested view.
If you do a poll among scientists and say, impossible,
we can understand anything.
Let me ask and give me a chance with this.
So I just spent a day at a company called Neuralink,
and what they do is try to design
what's called the brain-machine-brain-computer interface.
So they try to do thousands readings in the brain,
be able to read what the neurons are firing,
and then stimulate back, so two-way.
Do you think their dream is to expand the capacity
of the brain to attain information,
sort of increase the bandwidth
to which we can search Google kind of thing?
Do you think our cognitive capacity might be expanded,
our linguistic capacity,
our ability to reason might be expanded
by adding a machine into the picture?
It can be expanded in a certain sense,
but a sense that was known thousands of years ago,
a book expands your cognitive capacity.
Okay, so this could expand it too.
But it's not a fundamental expansion.
It's not totally new things could be understood.
Well, nothing that goes beyond
their native cognitive capacities,
just like you can't turn the visual system
into an insect system.
Well, I mean, the thought is, perhaps,
you can't directly, but you can map.
You could, but we already,
we know that without this experiment.
You could map what a bee sees
and present it in a form so that we could follow it.
In fact, every bee scientist does it.
But you don't think there's something greater than bees
that we can map and then all of a sudden discover
something, be able to understand a quantum world,
quantum mechanics, be able to start
to be able to make sense.
Students at MIT study and understand quantum mechanics.
But they always reduce it to the infant, the physical.
I mean, they don't really understand.
Oh, there's a thing, that may be another area
where there's just a limit to understanding.
We understand the theories,
but the world that it describes doesn't make any sense.
So, you know, the experiment,
the Schrödinger's cat, for example,
can understand the theory,
but as Schrödinger pointed out,
it's an unintelligible world.
One of the reasons why Einstein was always very skeptical
about quantum theory.
He described himself as a classical realist once,
and once intelligibility.
He has something in common with infants in that way.
So, back to linguistics, if you could humor me,
what are the most beautiful or fascinating aspects
of language or ideas in linguistics or cognitive science
that you've seen in a lifetime of studying language
and studying the human mind?
Well, I think the deepest property of language
and puzzling property that's been discovered
is what is sometimes called structure dependence.
We now understand it pretty well,
but it was puzzling for a long time.
I'll give you a concrete example.
So, suppose you say the guy who fixed the car
carefully packed his tools.
That's ambiguous, he could fix the car carefully
or carefully pack his tools.
Suppose you put carefully in front,
carefully the guy who fixed the car packed his tools,
then it's carefully packed, not carefully fixed.
And in fact, you do that even if it makes no sense.
So, suppose you say carefully,
the guy who fixed the car is tall.
You have to interpret it as carefully he's tall.
Even though that doesn't make any sense.
And notice that that's a very puzzling fact
because you're relating carefully
not to the linearly closest verb,
but to the linearly more remote verb.
A linear approach closeness is an easy computation,
but here you're doing a much more,
what looks like a more complex computation.
You're doing something that's taking you essentially
to the more remote thing.
It's now, if you look at the actual structure
of the sentence, where the phrases are and so on,
turns out you're picking out the structurally closest thing,
but the linearly more remote thing.
But notice that what's linear is 100% of what you hear.
You never hear structure, can't.
So what you're doing is, and instantly this is universal,
all constructions, all languages.
And what we're compelled to do is carry out
what looks like the more complex computation
on material that we never hear.
And we ignore 100% of what we hear
and the simplest computation.
But by now there's even a neural basis for this
that's somewhat understood.
And there's good theories by now
that explain why it's true.
That's a deep insight into the surprising nature
of language with many consequences.
Let me ask you about a field of machine learning,
deep learning.
There's been a lot of progress in neural networks based,
neural network based machine learning in the recent decade.
Of course, neural network research goes back many decades.
What do you think are the limits of deep learning
of neural network based machine learning?
Well, to give a real answer to that,
you'd have to understand the exact processes
that are taking place.
And those are pretty opaque.
So it's pretty hard to prove a theorem
about what can be done and what can't be done.
But I think it's reasonably clear.
I mean, putting technicalities aside,
what deep learning is doing is taking huge numbers
of examples and finding some patterns.
Okay, that could be interesting in some areas it is,
but we have to ask here a certain question.
Is it engineering or is it science?
Engineering in the sense of just trying to build something
that's useful or science in the sense
that it's trying to understand something
about elements of the world.
So it takes a Google parser.
We can ask that question.
Is it useful?
Yeah, it's pretty useful.
You know, I use a Google translator.
So on engineering grounds, it's kind of worth having,
like a bulldozer.
Does it tell you anything about human language?
Zero, nothing.
And in fact, it's very striking.
It's from the very beginning,
it's just totally remote from science.
So what is a Google parser doing?
It's taking an enormous text,
let's say the Wall Street Journal corpus,
and asking how close can we come
to getting the right description
of every sentence in the corpus?
Well, every sentence in the corpus
is essentially an experiment.
Each sentence that you produce is an experiment,
which is, am I a grammatical sentence?
The answer is usually yes.
So most of the stuff in the corpus
is grammatical sentences.
But now ask yourself, is there any science
which takes random experiments,
which are carried out for no reason whatsoever,
and tries to find out something from them?
Like if you're a, say, a chemistry PhD student,
you want to get a thesis, can you say,
well, I'm just going to do a lot of,
mix a lot of things together, no purpose, just,
and maybe I'll find something.
You'd be left out of the department.
Science tries to find critical experiments,
ones that answer some theoretical question.
Doesn't care about coverage of millions of experiments.
So it just begins by being very remote from science,
and it continues like that.
So the usual question that's asked
about, say, a Google parser,
is how well does it do, or some parser,
how well does it do on a corpus?
But there's another question that's never asked.
How well does it do on something
that violates all the rules of language?
So for example, take the structure dependence case
that I mentioned.
Suppose there was a language in which you used
a linear proximity as the mode of interpretation.
These deep learning had worked very easily on that.
In fact, much more easily on an actual language.
Is that a success?
No, that's a failure. From a scientific point of view,
it's a failure.
It shows that we're not discovering
the nature of the system at all,
because it does just as well or even better on things
that violate the structure of the system.
And it goes on from there.
It's not an argument against doing it.
It is useful to have devices like this.
So yes, neural networks are kind of approximators
that look, there's echoes of the behavioral debates,
right, behaviorism.
More than echoes.
Many of the people in deep learning say they've vindicated
Terry Sanyosky, for example, in his recent books.
This vindicates skinnerian behaviors.
It doesn't have anything to do with it.
Yes, but I think there's something
actually fundamentally different when the data set is huge,
but your point is extremely well taken.
But do you think we can learn, approximate
that interesting complex structure of language
with neural networks that will somehow help us
understand the science?
It's possible.
I mean, you find patterns that you hadn't noticed,
let's say, could be.
In fact, it's very much like a kind of linguistics
that's done, what's called corpus linguistics.
When you, suppose you have some language
where all the speakers have died out, but you have records.
So you just look at the records
and see what you can figure out from that.
It's much better than, it's much better
to have actual speakers where you can do critical experiments,
but if they're all dead, you can't do them.
So you have to try to see what you can find out
from just looking at the data that's around.
You can learn things.
Actually, paleoanthropology is very much like that.
You can't do a critical experiment
on what happened two million years ago.
So you kind of force just to take what data's around
and see what you can figure out from it.
Okay, it's a serious study.
So let me venture into another whole body of work
and philosophical question.
You've said that evil in society arises from institutions,
not inherently from our nature.
Do you think most human beings are good,
they have good intent,
or do most have the capacity for intentional evil
that depends on their upbringing,
depends on their environment, on context?
I wouldn't say that they don't arise from our nature.
Anything we do arises from our nature.
And the fact that we have certain institutions,
not others, is one mode in which human nature
has expressed itself.
But as far as we know, human nature could yield
many different kinds of institutions.
The particular ones that have developed
have to do with historical contingency,
who conquered whom and that sort of thing.
They're not rooted, they're not rooted in our nature
in the sense that they're essential to our nature.
So it's commonly argued that these days
that something like market systems
is just part of our nature,
but we know from a huge amount of evidence
that that's not true,
there's all kinds of other structures.
It's a particular fact of a moment of modern history.
Others have argued that the roots
of classical liberalism actually argue
that what's called sometimes an instinct for freedom,
an instinct to be free of domination
by illegitimate authority is the core of our nature.
That would be the opposite of this.
And we don't know,
we just know that human nature can accommodate both kinds.
If you look back at your life,
is there a moment in your intellectual life
or life in general that jumps from memory
that brought you happiness,
that you would love to relive again?
Sure, falling in love, having children.
What about, so you have put forward
into the world a lot of incredible ideas
in linguistics, in cognitive science,
in terms of ideas that just excites you
when it first came to you,
that you would love to relive those moments?
Well, I mean, when you make a discovery
about something that's exciting,
like say, even the observation of structured dependence
and gone from that, the explanation for it.
But the major things just seem like common sense.
So if you go back to take your question
about external and internal language,
you go back to say the 1950s,
almost entirely languages regarded an external object,
something outside the mind.
It just seemed obvious that that can't be true.
Like I said, there's something about you
that determines you're talking English,
not Swahili or something.
And, but that's not really a discovery,
that's just an observation that's transparent.
You might say it's kind of like the 17th century,
the beginnings of modern science, 17th century.
They came from being willing to be puzzled
about things that seemed obvious.
So it seems obvious that a heavy ball of ladle
fall faster than a light ball of ladle.
But Galileo was not impressed
by the fact that it seemed obvious.
So he wanted to know if it's true.
They carried out experiments,
actually thought experiments,
never actually carried them out,
which it can't be true.
And out of things like that, observations of that kind,
why does a ball fall to the ground instead of rising,
let's say, it seems obvious.
Do you start thinking about it?
Because why does it, why does steam rise, let's say?
And I think the beginnings of modern linguistics,
roughly in the 50s, are kind of like that,
just being willing to be puzzled about phenomena
that looked, from some point of view, obvious.
And for example, a kind of doctrine,
almost official doctrine of structural linguistics
in the 50s was that languages can differ
from one another in arbitrary ways.
And each one has to be studied on its own
without any presuppositions.
In fact, there were similar views among biologists
about the nature of organisms,
that each one is, they're so different.
When you look at them, that almost anything,
you could be almost anything.
Well, in both domains, it's been learned
that that's very far from true.
The very narrow constraints on what could be an organism
or what could be a language.
But these are, that's just the nature of inquiry.
Science in general, yeah, inquiry.
So one of the peculiar things about us human beings
is our mortality.
Ernest Becker explored it in general.
Do you ponder the value of mortality?
Do you think about your own mortality?
I used to when I was about 12 years old.
I wondered, I didn't care much about my own mortality,
but I was worried about the fact that
if my consciousness disappeared,
would the entire universe disappear?
That was frightening.
Did you ever find an answer to that question?
No, nobody's ever found an answer,
but I stopped being bothered by it.
It's kind of like Woody Allen in one of his films,
you may recall.
He starts, he goes to a shrink when he's a child
and the shrink asks him, what's your problem?
He says, I just learned that the universe is expanding.
I can't handle that.
And then another absurd question is,
what do you think is the meaning of our existence here,
our life on earth, our brief little moment in time?
That's something we answer by our own activities.
There's no general answer.
We determine what the meaning of it is.
The action determine the meaning.
Meaning in the sense of significance,
not meaning in the sense that chair means this,
but the significance of your life is something you create.
No, thank you so much for talking today.
It was a huge honor.
Thank you so much.
Thanks for listening to this conversation with No Chomsky
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