My name's Bradley Horowitz, I'm VP

of Social for Google, Social Product Management.

And I'm here today to welcome Sandy Pentland

to come in and speak with us.

I'm going to be brief.

I encourage you all to Google Sandy.

You will pull up his long list of credentials,

which include academic credentials, business

credentials, across many, many disciplines

for many, many years.

World Economic Forum, Forbes' Most Influential,

it goes on and on.

So I'm going to try to give you a little anecdote of something

that I don't think you'll get on the web.

Nothing too embarrassing.

I'm a student, both former and current, of Sandy's.

Former in the sense that I was a media lab Ph.D. student.

He was my adviser.

And current in the sense that I stay

closely attuned to everything that Sandy does.

As we were walking over here from building 1900,

we were sort of doing what old friends do,

which is play the name game and checking in

on all the old connections and friends that we share.

How's Roz doing?

How Stan doing?

How's Ali doing?

What about Fad?

And we went through them, and turns out

everybody's doing fine.

You know, many of you are here, actually in the second row,

in front row.

Many of you have gone off to become professors

at MIT or Berkeley or Georgia Tech.

And it was just so great.

And thinking about that for a moment,

I recognized that I was just walking

through one of the vintages, the sort of early '90s vintage

of Sandy's students who have all gone off to do great things.

And Sandy has consecutively piled

on top of that, round after round,

of graduate students and students that he has inspired.

And in addition to all of those lists of accomplishments,

one of the things that really touches me most

about Sandy and his work is that he's

such an inspirational educator.

He not only has enthusiasm for his own work,

he's able to impart that to others

and create generations of people that care passionately

about technology and science.

And it's just so great to be in the company, which we will all

get to share for an hour right now,

of a person who can inspire and lead that way.

And so with that, I'll hand it over to Sandy.

Welcome.

SANDY PENTLAND: Well, thank you.

[CLAPPING]

SANDY PENTLAND: Now, I'll have to inspire and cause

passion, which is actually part of what

I'm going to talk about.

So how does that happen?

So maybe this is good.

So I'm going to talk about two things.

One is basic science about who people

are, how we use electronic media, how we use face to face

media, how we evolved as a social species.

And then I want to move to how we can use this knowledge

to make things better, to have a more

sustainable digital ecology, to make government work.

Wouldn't that be amazing? [LAUGHS]

And so on and so forth.

And as Bradley mentioned, I do a lot of things.

I thought I'd stick this in.

I love this picture.

This is the boards back in the 1990s.

And that's Thad in the front there,

Thad Starner, who I think most of you know.

And then two other things I do that are of real relevancy

here, maybe three.

Is one is for the last five years,

I've run a group-- helped run a group at Davos--

around personal data, privacy, and big data.

And that's, of course, a very relevant topic for this crowd,

but particularly, going forward.

And the group includes people like the Chairman

of the Federal Trade Commission, the vice president of the EU,

Politburo members from China, et cetera, et cetera.

So it's a conversation between CEOs of major companies

and chief regulators and advocacy.

And I'll talk about that at then end

and where I think that things are going

and what you might want to do about it.

And I just joined the Google ATAP Board

because it used to be owned by Motorola,

but when Motorola got sold, they intelligently

moved the really creative interesting part over here

to Google.

And as Bradley mentioned, that started a bunch

of companies, which are doing well.

So the thing that I'm really concerned about,

the thing that's passionate, is making the world work better.

And a sort of story for this is about 15 years ago,

I was setting up a series of laboratories in India.

And, you know, we had huge government sponsorship.

We had a board of directors, which

are some of the brightest most successful people in the world.

And it was a complete disaster.

And it had to do with a lot of things.

It had to do with all of the sort of macho,

signaling charisma in the room with the board of directors.

But it also had to do with the way the government failed

to work, or did work.

And looking back on that, I can sort of

see that premonitions of the US Congress today.

All right?

So we went and visited the Indian Congress,

where we saw people throwing shoes at each other

and throwing cash in the air.

And we look at the US Congress today,

and it's somewhat similar, unfortunately.

So I want to make things better.

And what occurs to me is if we knew

how to make our organizations work,

then we could really do things.

Like we could solve global warming tomorrow

if we all knew how to sort of talk about it rationally,

come to a good decision, and then carry that through.

And the fact that that sounds like ludicrous fantasy--

oh, yeah, everybody agree.

Sure.

Not in our lifetime-- tells you just how profound

the problem is.

And that's why I think one of the most important things

that's happened in the last decade, something you've all

been part of, is this era of big data,

which is not about big at all.

It's about personal data.

Detailed data about the behavior of every person on Earth,

where they go, what they buy, what they say online,

all sorts of things like that.

Suddenly we could watch people the way,

say, you would watch an ant hill or Jane Goodall

would watch apes.

We can do that, and that has profound impact

that is hard to appreciate.

I made this little graph, which comes out

of-- inspired by Nadav's thesis here,

which is duration of observation.

These are social science experiments, and the biggest

medical experiments.

So this is like the Framingham heart study.

30 years, 30,000 people.

But they only talked to people like once every three years.

So the bit rate was like one number per month.

So you had no idea what these people were doing.

They could have been eating fried chicken all the time.

You don't know, right?

Or most of the things we know about psychology

come from down here.

This is a number of bits per second, duration.

This is a bunch of freshman in Psych 101

filling out some surveys.

And that's what we take to be social science,

political science, and medical science.

But now we have these new ways of doing things.

And so what in my group we've done

is we've built little badges, like you all

have little name badges.

And so we can actually know where you go

and who you talk to.

And we do this with organizations.

We'll track everybody for a month.

We never listen to the words, but we

do know the patterns of communication.

And I'll show you a little bit about that.

Similarly, we put software in phones,

and we look at the patterns of communication

within a community.

So I go into a community and give everybody brand

new phones.

And some of the people here have been integrally involved

in these experiments.

And we'll look at their Facebook activity, their credit card

record, their sleep pattern, their communication pattern,

who they hang with, who they call,

and ask, what do all this communication patterns

have to do with outcomes?

All right?

Do they spend too much?

What things do they choose to buy, and so forth.

And what you find from the big data,

and, of course, modern machine learning sorts of things,

is that you can build quantitative predictive models

of human behavior, which you all know.

But I think you know the wrong part.

And I'm going to tell you about the other part that's

much stronger than what you typically do, OK?

And so you can predict behavior.

And people go, well, wait a second.

What about free will?

That may not have occurred to you,

but that's a traditional thing to ask.

And I'll tell you a little bit about that along

the way because it turns out that a lot of our behavior

is very habitual, and that's the part

that we can model mathematically.

So the big picture here, and this

is part of the reason I got off onto this research,

is I go to places like Davos, and you

listen to the president of this and the CEO of that.

And when they talk about changing policy, talk

about doing anything, they use economics metaphors.

And the thing about [INAUDIBLE] economic metaphors

is that they're all about individuals.

So you've heard about rational individuals.

And everybody rags on the rational part.

I'm not going to do that.

I'm going to rag on the individual part, OK?

Because I don't think we are individuals.

What we desire, the ways we learn to go about doing it,

what's valuable, are consensual things.

So they actually are captured by this sort

of model, this independent model.

That matters because those interactions are

the sources, not only of fads and economic bubbles,

but they're really the social fabric that we live in.

So everybody knows about the invisible hand

that are led by the invisible hand

to advance the interest of society.

What that means is that markets are supposed to allocate things

efficiently and fairly, right?

If you've thought about it, you know

this doesn't work in the real world, [LAUGHS] OK?

And the question is, why?

So one of the things that-- there's

several things to say about this.

Most people think that this statement is something

that he made in "The Wealth of Nations."

And I'm just going to [INAUDIBLE]

"The Wealth of Nations."

But it's not.

He made it in a book called "Moral Sentiments," which

very few people read.

And it went on to say something very different.

It went on to say that "it's human nature

to exchange not only goods, but ideas, assistance, and favors.

And it's these exchanges that guide people

to create solutions for the good of the community."