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  • 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

  • just based on a few bricks,

  • that the writings of a culture are the archaeological 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 up 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 described in 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's 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 of 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 tells us 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 the 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 high-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 that we organize concepts in a hierarchy.

  • So for instance,

  • you can see that the scientific terms break down into two subcategories

  • of the astronomic and the physics 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 it actually 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 also 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 ask whether, 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 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 be translated

  • and generalized to a whole lot of different domains.

  • So in the same way that we asked about the past of human consciousness,

  • maybe the most challenging question we can pose to ourselves

  • is whether this can tell us something about the future of our own consciousness.

  • 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 same way many of us are now wearing sensors

  • 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 may go wrong with our minds.

  • And with Guillermo Cecchi,

  • who has been my brother in this adventure,

  • we took on this task.

  • And we did so by analyzing the recorded speech of 34 young people

  • who were at a high risk of developing schizophrenia.

  • 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 onset of 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 the other one.

  • 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 34 people,

  • the algorithm based on semantic coherence 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 at my computer

  • and I saw a bunch of tweets by Polo --

  • Polo had been my first student back in Buenos Aires,

  • and at the time he was living in New York.

  • And there was something in this tweets --

  • 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 in fact 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)

We have historical records that allow us to know how the ancient Greeks dressed,