We have historical records that allow us to know how the ancient Greeks dressed,
how they lived,
how they fought ...
but how did they think?
One [natural] idea is that the deepest aspects of human thought --
our ability to imagine,
to be conscious,
to dream --
have always been the same.
Another possibility
is that the social transformations that have shaped our culture
may have also changed the structural columns of human thought.
We may all have different opinions about this.
Actually, it's a long-standing philosophical debate.
But is this question even amenable to science?
Here I'd like to propose
that in the same way we can reconstruct how the ancient Greek cities looked like
just based on a few bricks,
that the writings of a culture are the archeological records --
the fossils of human thought.
And in fact,
doing some form of psychological analysis
of some of the most ancient books of human culture,
Julian Jaynes came in the '70s with a very wild and radical hypothesis ...
that only 3,000 years ago,
humans were what today we would call schizophrenics.
And he made this claim
based on the fact that the first humans [inscribing] these books
behaved consistently,
in different traditions and in different places of the world,
as if they were hearing and obeying voices
that they perceived as coming from the Gods,
or from the muses --
what today we would call hallucinations.
And only then,
as time went on,
they began to recognize that they were the creators --
the owners of these inner voices.
And with this they gained introspection:
the ability to think about their own thoughts.
So Jaynes' theory is that consciousness --
at least in the way we perceive it today,
where we feel that we are the pilots of our own existence --
is a quite recent cultural development.
And this theory is quite spectacular,
but it has an obvious problem
which is that it's built on just a few and very specific examples.
So the question is whether the theory
that introspection built up in human history only about 3,000 years ago
can be examined in a quantitative and objective manner.
And the problem on how to go about this is quite obvious.
It's not like Plato woke up one day
and then he wrote,
"Hello, I'm Plato
and as of today I have a fully introspective consciousness."
(Laughter)
And this still is actually what is the essence of the problem.
We need to find the emergence of a concept that's never said.
The word introspection does not appear a single time
in the books we want to analyze.
So our way to solve this is to build the space of words.
This is a huge space that contains all words
in such a way that they distance between any two of them
is indicative of how closely related they are.
So for instance,
you want the words dog and cat to be very close together,
but the words grapefruit and logarithm to be very far away.
And this has to be true for any two words within the space.
And there are different ways that we can construct the space of words.
One is just asking the experts,
a bit like we do with dictionaries.
Another possibility
is following the simple assumption
that when two words are related they tend to appear in the same sentences,
in the same paragraphs,
in the same documents,
more often than would be expected just by pure chance.
And this simple hypothesis,
this simple method,
with some computational tricks
that have to do with the fact
that this is a very complex and highly dimensional space,
turns out to be quite effective.
And just to give you a flavor of how well this works,
this is the result we get when we analyze this for some familiar words.
And you can see first
that words automatically organize into semantic neighborhoods.
So you get the fruits,
the body parts,
the computer parts,
the scientific terms
and so on.
The algorithm also identifies the reorganized concepts in a hierarchy.
So for instance,
you can see that the scientific terms break down into two subcategories
of the astronomic and the physic terms.
And then there are very fine things.
For instance,
the word astronomy,
which seems a bit bizarre where it is,
is actually exactly where it should be,
between what it is --
an actual science --
and between what it describes --
the astronomical terms.
And we could go on and on with this.
Actually if you stare at this for a while
and you just build random trajectories,
you will see that is feels well --
actually it feels a bit like doing poetry.
And this is because,
in a way,
walking in this space is like walking in the mind.
And the last thing
is that this algorithm identifies what are our intuitions
of which words should lead in the neighborhood of introspection.
So for instance,
words such as Self, Guilt, Reason, Emotion,
are very close to introspection,
but other words,
such as Red, Football, Candle, Banana,
are just very far away.
And so once we've built the space,
the question of the history of introspection,
or of the history of any concept
which before could seem abstract and somehow vague,
becomes concrete --
becomes amenable to quantitative science.
All that we have to do is take the books,
we digitize them
and we take this stream of words as a trajectory
and project them into the space,
and then we ask whether this trajectory spends significant time
circling closely to the concept of introspection.
And with this,
we could analyze the history of introspection
in the ancient Greek tradition,
for which we have the best available written record.
So what we did is we took all the books --
we just ordered them by time --
for each book we take the words
and we project them to the space,
and then we ask for each word how close it is to introspection,
and we just average that.
And then we understand that as time goes on and on,
these books get closer, and closer and closer
to the concept of introspection.
And this is exactly what happens in the ancient Greek tradition.
So you can see that for the oldest books in the Homeric tradition,
there is a small increase with books getting closer to introspection,
but about four centuries before Christ,
this starts ramping up very rapidly
to an almost five-fold increase
of books getting closer, and closer and closer
to the concept of introspection.
And one of the nice things about this
is that now we can ask
whether this is also true in a different independent tradition.
So we just ran this same analysis on the Judeo Christian tradition,
and we got virtually the same pattern.
Again you see a small increase for the oldest books in the old testament,
and then it increases much more rapidly
in the new books of the new testament,
and then we get the peak of introspection
in the work Confessions of Saint Augustine,
about four centuries after Christ.
And this was very important,
because Saint Augustine had been recognized
by scholars, philologists, historians,
as one of the founders of introspection.
Actually, some believe him to be the father of modern psychology.
So our algorithm --
which has the virtue of being quantitative,
of being objective,
and of course of being extremely fast,
it just runs in a fraction of a second --
can capture some of the most important conclusions
of this long tradition of investigation.
And this is in a way, one of the beauties of science,
which is that now this idea can translated
and generalized to a whole lot of different domains.
So in the same way that we asked about the past of human conciousness,
maybe the most challenging question we can pose to ourselves,
is whether this can tell us something about the future of our unconciousness.
To put it more precisely,
whether the words we say today
can tell us something of where our minds will be in a few days,
in a few months,
or a few years from now.
And in the way many of us are now wearing censors
that detect our heart rate,
our respiration,
our genes,
on the hopes that this may help us prevent diseases,
we can ask whether monitoring and analyzing the words we speak --
we tweet,
we email,
we write --
can tell us ahead of time whether something will go wrong with our minds.
And with Guillermo Cecci,
who has been my brother in this adventure,
we took on this task.
And we did so by analyzing the recorded speech for 44 young people
who were at a high risk of developing schizophenia.
And so what we did is we measured speech at day one
and then we asked
whether the properties of the speech could predict --
within a window of almost three years --
the future development of psychosis.
But despite our hopes,
we got failure after failure.
There was just not enough information in semantics
to predict the future organization of the mind.
It was good enough
to distinguish between a group of schizophrenics and a control group,
a bit like we had done for the ancient texts,
but not to predict the future onto the psychosis.
But then we realized
that maybe the most important thing was not so much what they were saying
but how they were saying it.
More specifically,
it was not in which semantic neighborhoods the words were,
but how far and fast they jumped from one semantic neighborhood to another.
And so we came up with this measure,
which we termed Semantic Coherence,
which essentially measures
the persistence of speech within one semantic topic,
within one semantic category.
And it turned out to be
that for this group of 44 people,
the algorithm based on semantic cohernece
could predict with 100 percent accuracy
who developed psychosis and who will not.
And this was something that could not be achieved --
not even close --
with all the other existing clinical measures.
And I remember vividly while I was working on this,
I was sitting on my computer
and I saw a bunch of tweets by Polo.
Polo has been my first student back in Buenos Aires
and at the time he was living in New York.
And there was something in this tweet --
I could not tell exactly what because nothing was said explicitly --
but I got this strong hunch,
this strong intuition that something was going wrong.
So I picked up the phone and I called Polo,
and he was not feeling well.
And this simple fact that reading in between the lines
I could sense through words his feelings,
was a simple but very effective way to help.
What I tell you today
is that we're getting close to understanding
how we can convert this intuition that we all have,
that we all share,
into an algorithm.
And in doing so,
we may be seeing in the future a very different form of mental health,
based on objective, quantitative and automated analysis
of the words we write,
of the words we say.
Gracias.
(Applause)