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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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out ability to imagine,
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to be concious,
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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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make us also change 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 longstanding
philosophical debate.
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But is this question
even amenable to science?
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Here I'd like to propose that in the same way
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that in the same way
that we can reconstruct
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how the ancient Greek cities looked like,
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just based on a few bricks,
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that the writings of a culture
are the archealogical records --
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the fossils --
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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 James came 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 today
what we'd call, schizophrenics.
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And he made this claim
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based on the fact that the first humans
writing these books 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'd call hallucinations.
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And only then,
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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' theory is that conciousness,
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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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because 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
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whether the theory that introspection
built up only about 3,000 years ago,
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can be examined in a quantitative
and objective way.
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And the problem on how
to go about this is quite obvious.
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It's not like Plato woke up one day
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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 still is 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 they 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
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that when two words are related
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 highly 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,
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the body parts,
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the computer parts,
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the scientific terms
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and so on.
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The algorithm also identifies
the reorganized 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 physic terms.
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And then their are very fine things.
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For instance,
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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 awhile
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and you just build random trajectories,
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you will see that is feels well --
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actually it feels a bit like doing poetry.
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And this is because in way,
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walking in this space
is like walking in the mind.
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And last thing 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 this 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 this 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 can 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 then we understand
that 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
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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 work 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
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by scholars, 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 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 conciousness,
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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 unconciousness.
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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 way many of us
are now wearing censors
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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,
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we email,
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we write --
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can tell us ahead of time whether
something will go wrong with our minds.
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And with Guillermo Cecci,
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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 for 44 young people
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who were at a high risk
of developing schizophenia.
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And so what we did is we
measured speech at day one
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and then we asked
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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
onto the 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
from one semantic neighborhood to another.
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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
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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
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that for this group of 44 people,
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the algorithm based on semantic cohernece
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could predict 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 on my computer
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and I saw a bunch of tweets by Polo.
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Polo has 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 tweet --
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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 he was not feeling well.
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And this simple fact 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)