Scholars have long contemplated the connection between language and
thought—and to what degree the two are intertwined—by asking whether
language is somehow an essential prerequisite for thinking.
British philosopher and mathematician Bertrand Russell answered the
question with a flat yes, asserting that language’s very purpose is “to
make possible thoughts which could not exist without it.” But even a
cursory glance around the natural world suggests why Russell may be wrong:
No words are needed for animals to perform all sorts of problem-solving
challenges that demonstrate high-level cognition. Chimps can outplay humans
in a strategy game, and New Caledonian Crows make their own tools that
enable them to capture prey.
Still, humans perform cognitive tasks at a level of sophistication
not seen in chimps—we can solve differential equations or compose majestic
symphonies. Is language needed in some form for these species-specific
achievements? Do we require words or syntax as scaffolding to construct the
things we think about? Or do the brain’s cognitive regions devise fully
baked thoughts that we then convey using words as a medium of communication?
Evelina Fedorenko, a neuroscientist who studies language at the
McGovern Institute for Brain Research at the Massachusetts Institute of
Technology, has spent many years trying to answer these questions. She
remembers being a Harvard University undergraduate in the early 2000s, when
the language-begets-thought hypothesis was still highly prominent in
academia. She herself became a believer.
When Fedorenko began her research 15 years ago, a time when new
brain-imaging techniques had become widely available, she wanted to
evaluate this idea with the requisite rigor. She recently co-authored a
perspective article in Nature that includes a summary of her findings over
the ensuing years. It makes clear that the jury is no longer out, in
Fedorenko’s view: language and thought are, in fact, distinct entities that
the brain processes separately. The highest levels of cognition—from novel
problem-solving to social reasoning—can proceed without an assist from
words or linguistic structures.
Language works a little like telepathy in allowing us to communicate
our thoughts to others and to pass to the next generation the knowledge and
skills essential for our hypersocial species to flourish. But at the same
time, a person with aphasia, who are sometimes unable to utter a single
word, can still engage in an array of cognitive tasks fundamental to
thought. Scientific American talked to Fedorenko about the language-thought
divide and the prospects of artificial intelligence tools such as large
language models for continuing to explore interactions between thinking and
speaking.
[An edited transcript of the interview follows.]
How did you decide to ask the question of whether language and thought are
separate entities?
Honestly, I had a very strong intuition that language is pretty critical to
complex thought. In the early 2000s I really was drawn to the hypothesis
that maybe humans have some special machinery that is especially well
suited for computing hierarchical structures. And language is a prime
example of a system based on hierarchical structures: words combine into
phrases and phrases combine into sentences.
And a lot of complex thought is based on hierarchical structures. So, I
thought, ‘Well, I’m going to go and find this brain region that processes
hierarchical structures of language.’ There had been a few claims at the
time that some parts of the left frontal cortex are that structure.
But a lot of the methods that people were using to examine overlap in the
brain between language and other domains weren’t that great. And so, I
thought I would do it better. And then, as often happens in science, things
just don’t work the way you imagine they might. I searched for evidence for
such a brain region—and it doesn’t exist.(K R And yet we do not address
thescience as myth nor we disown as ignorant)
You find this very clear separation between brain regions that compute
hierarchical structures in language and brain regions that help you do the
same kind of thing in math or music. A lot of science starts out with some
hypotheses that are often based on intuitions or on prior beliefs.
My original training was in the [tradition of linguist Noam Chomsky],
(KR: YM knows it and about others…) where the dogma has always been that we
use language for thinking: to think is why language evolved in our species.
And so, this is the expectation I had from that training. But you just
learn, when you do science, that most of the time you’re wrong—and that’s
great because we learn how things actually work in reality.
What evidence did you find that thought and language are separate systems?
The evidence comes from two separate methods. One is basically a very old
method that scientists have been using for centuries: looking at deficits
in different abilities—for instance, in people with brain damage.
Using this approach, we can look at individuals who have impairments in
language—some form of aphasia. Aphasia has been studied as a condition for
centuries. For the question of how language relates to systems of thought,
the most informative cases are cases of really severe impairments,
so-called global aphasia, where individuals basically lose completely their
ability to understand and produce language as a result of massive damage to
the left hemisphere of the brain. You can ask whether people who have these
severe language impairments can perform tasks that require thinking. You
can ask them to solve some math problems or to perform a social reasoning
test, and all of the instructions, of course, have to be nonverbal because
they can’t understand linguistic information anymore. Scientists have a lot
of experience working with populations that don’t have language—studying
preverbal infants or studying nonhuman animal species. So, it’s definitely
possible to convey instructions in a way that’s nonverbal. And the key
finding from this line of work is that there are people with severe
language impairments who nonetheless seem totally fine on all cognitive
tasks that we’ve tested them on so far.
There are individuals who have been tested on many, many different kinds of
tasks, including tasks that involve what you may call thinking, such as
solving math problems or logic puzzles or reasoning about what somebody
else believes or reasoning about the physical world. So that’s one big
chunk of evidence from these populations of people with aphasia.
What is the other method?
A nicely complementary approach, which started in the 1980s and 1990s, is a
brain-imaging approach. We can measure blood flow changes when people
engage in different tasks and ask questions about whether the two systems
are distinct or overlapping—for example, whether your language regions
overlap with regions that help you solve math problems. These brain-imaging
tools are really good for these questions. But before I could ask these
questions, I needed a way to robustly and reliably identify language areas
in individual brains, so I spent the first bunch of years of my career
developing tools to do this.
And once we have a way of finding these language regions, and we
know that these are the regions that, when damaged in adulthood, lead to
conditions such as aphasia, we can then ask whether these language regions
are active when people engage in various thinking tasks. So you can come
into the lab, and I can put you in the scanner, find your language regions
by asking you to perform a short task that takes a few minutes—and then I
can ask you to do some logic puzzles or sudoku or some complex working
memory tasks or planning and decision-making. And then I can ask whether
the regions that we know process language are working when you’re engaging
in these other kinds of tasks. There are now dozens of studies that we’ve
done looking at all sorts of nonlinguistic inputs and tasks, including many
thinking tasks. We find time and again that the language regions are
basically silent when people engage in these thinking activities.
`So what is the role of language, if not for thinking?
What I’m doing right now is sharing some knowledge that I have that you may
have only had a partial version of—and once I transmit it to you through
language, you can update your knowledge and have that in your mind as well.
So it’s basically like a shortcut for telepathy. We can’t read each other’s
mind. But we can use this tool called language, which is a flexible way to
communicate our inner states, to transmit information to each other.
And in fact, most of the things that you probably learned about the world,
you learned through language and not through direct experience with the
world. So language is very useful. You can easily imagine how it would
confer evolutionary advantages: by facilitating cooperative activities,
transmitting knowledge about how to build tools and conveying social
knowledge. As people started living in larger groups, it became more
important to keep track of various social relationships. For example, I can
tell you, “Oh, I don’t trust that guy.” Also, it’s very hard to transmit
knowledge to future generations, and language allows us to do that very
effectively.
In line with the idea that we have language to communicate, there is
accumulating evidence from the past few decades that shows that various
properties that human languages have—there are about 7,000 of them spoken
and signed across the world—are optimized for efficiently transmitting
information, making things easy to perceive, easy to understand, easy to
produce and easy to learn for kids.
Is language what makes humans special?
We know from brain evolution that many parts of the cortical sheet [the
outer layer of the brain] expanded a lot in humans. These parts of the
brain contain several distinct functional systems. Language is one of them.
But there’s also a system that allows us to reason about other minds.
There’s a system that supports novel problem-solving. There’s a system that
allows us to integrate information across extended contexts in time—for
example, chaining a few events together. It’s most likely that what makes
us human is not one “golden ticket,” as some call it. It’s not one thing
that happened; it’s more likely that a whole bunch of systems got more
sophisticated, taking up larger chunks of cortex and allowing for more
complex thoughts and behaviors.
Do the language and thinking systems interact with each other?
There aren’t great tools in neuroscience to study intersystem interactions
between language and thought. But there are interesting new opportunities
that are opening up with advances in AI where we now have a model system to
study language, which is in the form of these large language models such as
GPT-2 and its successors. These models do language really well, producing
perfectly grammatical and meaningful sentences. They’re not so good at
thinking, which is nicely aligning with the idea that the language system
by itself is not what makes you think.
But we and many other groups are doing work in which we take some version
of an artificial neural network language model as a model of the human
language system. And then we try to connect it to some system that is more
like what we think human systems of thought look like—for example, a
symbolic problem-solving system such as a math app. With these artificial
intelligence tools, we can at least ask, “What are the ways in which a
system of thought, a system of reasoning, can interact with a system that
stores and uses linguistic representations?” These so-called neurosymbolic
approaches provide an exciting opportunity to start tackling these
questions.
So what do large language models do to help us understand the neuroscience
of how language works?
They’re basically the first model organism for researchers studying the
neuroscience of language. They are not a biological organism, but until
these models came about, we just didn’t have anything other than the human
brain that does language. And so what’s happening is incredibly exciting.
You can do stuff on models that you can’t do on actual biological systems
that you’re trying to understand. There are many, many questions that we
can now ask that have been totally out of reach: for example, questions
about development.
In humans, of course, you cannot manipulate linguistic input that children
get. You cannot deprive kids of language, or restrict their input in some
way, and see how they develop. But you can build these models that are
trained on only particular kinds of linguistic input or are trained on
speech inputs as opposed to textual inputs. And then you can see whether
models trained in particular ways better recapitulate what we see in humans
with respect to their linguistic behavior or brain responses to language.
So just as neuroscientists have long used a mouse or a macaque as a model
organism, we can now use these in silico models, which are not biological
but very powerful in their own way, to try to understand some aspects of
how language develops or is processed or decays in aging or whatnot.
We have a lot more access to these models’ internals. The methods we have
for messing with the brain, at least with the human brain, are much more
limited compared with what we can do with these models.
>From another group K Rajaram IRS 241024
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