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We have historical records that allow us
to know how the ancient Greeks dressed,
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how they lived,
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how they fought ...
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but how did they think?
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One natural idea is that the deepest
aspects of human thought --
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our ability to imagine,
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to be conscious,
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to dream --
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have always been the same.
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Another possibility
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is that the social transformations
that have shaped our culture
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may have also changed
the structural columns of human thought.
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We may all have different
opinions about this.
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Actually, it's a long-standing
philosophical debate.
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But is this question
even amenable to science?
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Here I'd like to propose
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that in the same way we can reconstruct
how the ancient Greek cities looked
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just based on a few bricks,
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that the writings of a culture
are the archaeological records,
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the fossils, of human thought.
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And in fact,
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doing some form of psychological analysis
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of some of the most ancient
books of human culture,
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Julian Jaynes came up in the '70s
with a very wild and radical hypothesis:
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that only 3,000 years ago,
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humans were what today
we would call schizophrenics.
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And he made this claim
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based on the fact that the first
humans described in these books
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behaved consistently,
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in different traditions
and in different places of the world,
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as if they were hearing and obeying voices
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that they perceived
as coming from the Gods,
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or from the muses ...
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what today we would call hallucinations.
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And only then, as time went on,
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they began to recognize
that they were the creators,
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the owners of these inner voices.
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And with this, they gained introspection:
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the ability to think
about their own thoughts.
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So Jaynes's theory is that consciousness,
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at least in the way we perceive it today,
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where we feel that we are the pilots
of our own existence --
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is a quite recent cultural development.
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And this theory is quite spectacular,
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but it has an obvious problem
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which is that it's built on just a few
and very specific examples.
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So the question is whether the theory
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that introspection built up in human
history only about 3,000 years ago
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can be examined in a quantitative
and objective manner.
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And the problem of how
to go about this is quite obvious.
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It's not like Plato woke up one day
and then he wrote,
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"Hello, I'm Plato,
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and as of today, I have
a fully introspective consciousness."
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(Laughter)
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And this tells us actually
what is the essence of the problem.
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We need to find the emergence
of a concept that's never said.
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The word introspection
does not appear a single time
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in the books we want to analyze.
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So our way to solve this
is to build the space of words.
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This is a huge space
that contains all words
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in such a way that the distance
between any two of them
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is indicative of how
closely related they are.
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So for instance,
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you want the words "dog" and "cat"
to be very close together,
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but the words "grapefruit" and "logarithm"
to be very far away.
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And this has to be true
for any two words within the space.
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And there are different ways
that we can construct the space of words.
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One is just asking the experts,
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a bit like we do with dictionaries.
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Another possibility
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is following the simple assumption
that when two words are related,
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they tend to appear in the same sentences,
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in the same paragraphs,
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in the same documents,
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more often than would be expected
just by pure chance.
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And this simple hypothesis,
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this simple method,
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with some computational tricks
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that have to do with the fact
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that this is a very complex
and high-dimensional space,
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turns out to be quite effective.
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And just to give you a flavor
of how well this works,
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this is the result we get when
we analyze this for some familiar words.
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And you can see first
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that words automatically organize
into semantic neighborhoods.
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So you get the fruits, the body parts,
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the computer parts,
the scientific terms and so on.
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The algorithm also identifies
that we organize concepts in a hierarchy.
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So for instance,
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you can see that the scientific terms
break down into two subcategories
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of the astronomic and the physics terms.
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And then there are very fine things.
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For instance, the word astronomy,
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which seems a bit bizarre where it is,
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is actually exactly where it should be,
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between what it is,
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an actual science,
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and between what it describes,
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the astronomical terms.
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And we could go on and on with this.
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Actually, if you stare
at this for a while,
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and you just build random trajectories,
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you will see that it actually feels
a bit like doing poetry.
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And this is because, in a way,
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walking in this space
is like walking in the mind.
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And the last thing
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is that this algorithm also identifies
what are our intuitions,
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of which words should lead
in the neighborhood of introspection.
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So for instance,
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words such as "self," "guilt,"
"reason," "emotion,"
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are very close to "introspection,"
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but other words,
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such as "red," "football,"
"candle," "banana,"
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are just very far away.
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And so once we've built the space,
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the question of the history
of introspection,
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or of the history of any concept
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which before could seem abstract
and somehow vague,
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becomes concrete --
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becomes amenable to quantitative science.
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All that we have to do is take the books,
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we digitize them,
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and we take this stream
of words as a trajectory
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and project them into the space,
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and then we ask whether this trajectory
spends significant time
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circling closely to the concept
of introspection.
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And with this,
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we could analyze
the history of introspection
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in the ancient Greek tradition,
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for which we have the best
available written record.
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So what we did is we took all the books --
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we just ordered them by time --
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for each book we take the words
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and we project them to the space,
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and then we ask for each word
how close it is to introspection,
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and we just average that.
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And as time goes on and on,
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these books get closer,
and closer and closer
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to the concept of introspection.
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And this is exactly what happens
in the ancient Greek tradition.
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So you can see that for the oldest books
in the Homeric tradition,
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there is a small increase with books
getting closer to introspection.
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But about four centuries before Christ,
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this starts ramping up very rapidly
to an almost five-fold increase
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of books getting closer,
and closer and closer
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to the concept of introspection.
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And one of the nice things about this
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is that now we can ask
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whether this is also true
in a different, independent tradition.
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So we just ran this same analysis
on the Judeo-Christian tradition,
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and we got virtually the same pattern.
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Again, you see a small increase
for the oldest books in the Old Testament,
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and then it increases much more rapidly
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in the new books of the New Testament.
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And then we get the peak of introspection
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in "The Confessions of Saint Augustine,"
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about four centuries after Christ.
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And this was very important,
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because Saint Augustine
had been recognized by scholars,
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philologists, historians,
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as one of the founders of introspection.
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Actually, some believe him to be
the father of modern psychology.
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So our algorithm,
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which has the virtue
of being quantitative,
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of being objective,
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and of course of being extremely fast --
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it just runs in a fraction of a second --
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can capture some of the most
important conclusions
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of this long tradition of investigation.
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And this is in a way
one of the beauties of science,
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which is that now this idea
can be translated
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and generalized to a whole lot
of different domains.
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So in the same way that we asked
about the past of human consciousness,
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maybe the most challenging question
we can pose to ourselves
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is whether this can tell us something
about the future of our own consciousness.
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To put it more precisely,
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whether the words we say today
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can tell us something
of where our minds will be in a few days,
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in a few months
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or a few years from now.
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And in the same way many of us
are now wearing sensors
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that detect our heart rate,
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our respiration,
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our genes,
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on the hopes that this may
help us prevent diseases,
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we can ask whether monitoring
and analyzing the words we speak,
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we tweet, we email, we write,
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can tell us ahead of time whether
something may go wrong with our minds.
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And with Guillermo Cecchi,
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who has been my brother in this adventure,
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we took on this task.
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And we did so by analyzing
the recorded speech of 34 young people
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who were at a high risk
of developing schizophrenia.
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And so what we did is,
we measured speech at day one,
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and then we asked whether the properties
of the speech could predict,
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within a window of almost three years,
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the future development of psychosis.
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But despite our hopes,
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we got failure after failure.
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There was just not enough
information in semantics
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to predict the future
organization of the mind.
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It was good enough
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to distinguish between a group
of schizophrenics and a control group,
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a bit like we had done
for the ancient texts,
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but not to predict the future
onset of psychosis.
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But then we realized
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that maybe the most important thing
was not so much what they were saying,
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but how they were saying it.
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More specifically,
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it was not in which semantic
neighborhoods the words were,
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but how far and fast they jumped
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from one semantic neighborhood
to the other one.
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And so we came up with this measure,
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which we termed semantic coherence,
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which essentially measures the persistence
of speech within one semantic topic,
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within one semantic category.
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And it turned out to be
that for this group of 34 people,
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the algorithm based on semantic
coherence could predict,
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with 100 percent accuracy,
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who developed psychosis and who will not.
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And this was something
that could not be achieved --
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not even close --
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with all the other
existing clinical measures.
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And I remember vividly,
while I was working on this,
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I was sitting at my computer
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and I saw a bunch of tweets by Polo --
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Polo had been my first student
back in Buenos Aires,
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and at the time
he was living in New York.
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And there was something in this tweets --
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I could not tell exactly what
because nothing was said explicitly --
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but I got this strong hunch,
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this strong intuition,
that something was going wrong.
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So I picked up the phone,
and I called Polo,
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and in fact he was not feeling well.
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And this simple fact,
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that reading in between the lines,
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I could sense,
through words, his feelings,
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was a simple, but very
effective way to help.
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What I tell you today
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is that we're getting
close to understanding
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how we can convert this intuition
that we all have,
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that we all share,
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into an algorithm.
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And in doing so,
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we may be seeing in the future
a very different form of mental health,
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based on objective, quantitative
and automated analysis
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of the words we write,
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of the words we say.
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Gracias.
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(Applause)