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(Video) Nicholas Negroponte: 
Can we switch to the video disc,

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which is in play mode?

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I'm really interested in how you put people and computers together.

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We will be using the TV screens or their equivalents

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for electronic books of the future.

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(Music, crosstalk)

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Very interested in touch-sensitive displays,

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high-tech, high-touch, not having
to pick up your fingers to use them.

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There is another way where computers

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touch people: wearing, physically wearing.

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Suddenly on September 11th,

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the world got bigger.

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NN: Thank you. (Applause)

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Thank you.

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When I was asked to do this,

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I was also asked to look at all 14 TED Talks

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that I had given,

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chronologically.

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The first one was actually two hours.

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The second one was an hour,

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and then they became half hours,

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and all I noticed was my bald spot getting bigger.

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(Laughter)

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Imagine seeing your life, 30 years of it, go by,

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and it was, to say the least,

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for me, quite a shocking experience.

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So what I'm going to do in my time

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is try and share with you what happened

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during the 30 years,

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and then also make a prediction,

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and then tell you a little bit

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about what I'm doing next.

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And I put on a slide

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where TED 1 happened in my life.

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And it's rather important

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because I had done 15 years of research before it,

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so I had a backlog, so it was easy.

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It's not that I was Fidel Castro

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and I could talk for two hours,

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or Bucky Fuller.

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I had 15 years of stuff,

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and the Media Lab was about to start.

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So that was easy.

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But there are a couple of things

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about that period

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and about what happened that are

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really quite important.

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One is that

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it was a period when computers

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weren't yet for people.

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And the other thing that sort of happened

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during that time is that

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we were considered sissy computer scientists.

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We weren't considered the real thing.

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So what I'm going to show you is, in retrospect,

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a lot more interesting and a lot more accepted

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than it was at the time.

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So I'm going to characterize the years

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and I'm even going to go back

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to some very early work of mine,

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and this was the kind of stuff I was doing in the '60s:

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very direct manipulation,

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very influenced as I studied architecture

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by the architect Moshe Safdie,

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and you can see that we even built robotic things

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that could build habitat-like structures.

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And this for me was

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not yet the Media Lab,

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but was the beginning of what I'll call

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sensory computing,

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and I pick fingers

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partly because everybody thought it was ridiculous.

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Papers were published

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about how stupid it was to use fingers.

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Three reasons: One was they were low-resolution.

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The other is your hand would occlude

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what you wanted to see,

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and the third, which was the winner,

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was that your fingers would get the screen dirty,

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and hence, fingers would never be

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a device that you'd use.

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And this was a device we built in the '70s,

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which has never even been picked up.

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It's not just touch sensitive,

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it's pressure sensitive.

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(Video) Voice: Put a yellow circle there.

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NN: Later work, and again this was before TED 1 —

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(Video) Voice: Move that west of the diamond.

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Create a large green circle there.

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Man: Aw, shit.

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NN: — was to sort of do interface concurrently,

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so when you talked and you pointed

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and you had, if you will,

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multiple channels.

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Entebbe happened.

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1976, Air France was hijacked,

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taken to Entebbe,

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and the Israelis not only did an extraordinary rescue,

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they did it partly because they had practiced

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on a physical model of the airport,

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because they had built the airport,

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so they built a model in the desert,

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and when they arrived at Entebbe,

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they knew where to go because
they had actually been there.

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The U.S. government asked some of us, '76,

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if we could replicate that computationally,

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and of course somebody like myself says yes.

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Immediately, you get a contract,

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Department of Defense,

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and we built this truck and this rig.

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We did sort of a simulation,

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because you had video discs,

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and again, this is '76.

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And then many years later,

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you get this truck,

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and so you have Google Maps.

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Still people thought,

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no, that was not serious computer science,

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and it was a man named Jerry Wiesner,

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who happened to be the president of MIT,

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who did think it was computer science.

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And one of the keys for anybody

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who wants to start something in life:

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Make sure your president is part of it.

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So when I was doing the Media Lab,

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it was like having a gorilla in the front seat.

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If you were stopped for speeding

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and the officer looked in the window

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and saw who was in the passenger seat,

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then, "Oh, continue on, sir."

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And so we were able,

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and this is a cute, actually, device, parenthetically.

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This was a lenticular photograph of Jerry Wiesner

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where the only thing that changed in the photograph

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were the lips.

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So when you oscillated that little piece

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of lenticular sheet with his photograph,

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it would be in lip sync

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with zero bandwidth.

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It was a zero-bandwidth teleconferencing system

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at the time.

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So this was the Media Lab's —

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this is what we said we'd do,

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that the world of computers, publishing,

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and so on would come together.

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Again, not generally accepted,

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but very much part of TED in the early days.

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And this is really where we were headed.

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And that created the Media Lab.

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One of the things about age

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is that I can tell you with great confidence,

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I've been to the future.

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I've been there, actually, many times.

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And the reason I say that is,

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how many times in my life have I said,

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"Oh, in 10 years, this will happen,"

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and then 10 years comes.

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And then you say, "Oh, in
five years, this will happen."

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And then five years comes.

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So I say this a little bit with having felt

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that I'd been there a number of times,

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and one of the things that is most quoted

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that I've ever said

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is that computing is not about computers,

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and that didn't quite get enough traction,

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and then it started to.

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It started to because people caught on

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that the medium wasn't the message.

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And the reason I show this car

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in actually a rather ugly slide

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is just again to tell you the kind of story

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that characterized a little bit of my life.

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This is a student of mine

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who had done a Ph.D. called "Backseat Driver."

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It was in the early days of GPS,

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the car knew where it was,

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and it would give audio instructions

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to the driver, when to turn right, 
when to turn left and so on.

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Turns out, there are a lot of things

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in those instructions that back in that period

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were pretty challenging,

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like what does it mean, take the next right?

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Well, if you're coming up on a street,

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the next right's probably the one after,

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and there are lots of issues,

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and the student did a wonderful thesis,

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and the MIT patent office said "Don't patent it.

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It'll never be accepted.

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The liabilities are too large.

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There will be insurance issues.

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Don't patent it."

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So we didn't,

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but it shows you how people, again, at times,

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don't really look at what's happening.

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Some work, and I'll just go
through these very quickly,

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a lot of sensory stuff.

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You might recognize a young Yo-Yo Ma

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and tracking his body for playing

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the cello or the hypercello.

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These fellows literally walked 
around like that at the time.

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It's now a little bit more discreet

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and more commonplace.

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And then there are at least three heroes

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I want to quickly mention.

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Marvin Minsky, who taught me a lot

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about common sense,

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and I will talk briefly about Muriel Cooper,

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who was very important to Ricky Wurman

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and to TED, and in fact, when she got onstage,

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she said, the first thing she said was,

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"I introduced Ricky to Nicky."

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And nobody calls me Nicky

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and nobody calls Richard Ricky,

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so nobody knew who she was talking about.

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And then, of course, Seymour Papert,

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who is the person who said,

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"You can't think about thinking

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unless you think about thinking about something."

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And that's actually — you can unpack that later.

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It's a pretty profound statement.

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I'm showing some slides

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that were from TED 2,

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a little silly as slides, perhaps.

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Then I felt television really was about displays.

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Again, now we're past TED 1,

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but just around the time of TED 2,

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and what I'd like to mention here is,

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even though you could imagine

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intelligence in the device,

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I look today at some of the work

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being done about the Internet of Things,

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and I think it's kind of tragically pathetic,

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because what has happened is people take

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the oven panel and put it on your cell phone,

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or the door key onto your cell phone,

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just taking it and bringing it to you,

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and in fact that's actually what you don't want.

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You want to put a chicken in the oven,

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and the oven says, "Aha, it's a chicken,"

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and it cooks the chicken.

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"Oh, it's cooking the chicken for Nicholas,

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and he likes it this way and that way."

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So the intelligence, instead of being in the device,

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we have started today

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to move it back onto the cell phone

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or closer to the user,

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not a particularly enlightened view

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of the Internet of Things.

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Television, again, television what I said today,

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that was back in 1990,

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and the television of tomorrow

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would look something like that.

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Again, people, but they laughed cynically,

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they didn't laugh with much appreciation.

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Telecommunications in the 1990s,

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George Gilder decided that he would call this diagram

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the Negroponte switch.

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I'm probably much less famous than George,

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so when he called it the Negroponte switch, it stuck,

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but the idea of things that came in the ground

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would go in the air and stuff in the air

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would go into the ground

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has played itself out.

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That is the original slide from that year,

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and it has worked in lockstep obedience.

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We started Wired magazine.

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Some people, I remember we shared

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the reception desk periodically,

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and some parent called up irate that his son

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had given up Sports Illustrated

271
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to subscribe for Wired,

272
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and he said, "Are you some
porno magazine or something?"

273
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and couldn't understand why his son

274
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would be interested in Wired, at any rate.

275
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I will go through this a little quicker.

276
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This is my favorite, 1995,

277
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back page of Newsweek magazine.

278
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Okay. Read it. (Laughter)

279
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["Nicholas Negroponte, director of the MIT Media Lab, predicts that we'll soon buy books and newspapers straight over the Internet. Uh, sure."
—Clifford Stoll, Newsweek, 1995]

280
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You must admit that gives you,

281
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at least it gives me pleasure

282
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when somebody says how dead wrong you are.

283
00:12:29,430 --> 00:12:31,576
"Being Digital" came out.

284
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For me, it gave me an opportunity

285
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to be more in the trade press

286
00:12:36,419 --> 00:12:39,690
and get this out to the public,

287
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and it also allowed us to build the new Media Lab,

288
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which if you haven't been to, visit,

289
00:12:44,638 --> 00:12:47,657
because it's a beautiful piece of architecture

290
00:12:47,657 --> 00:12:50,482
aside from being a wonderful place to work.

291
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So these are the things we were saying in those TEDs.

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[Today, multimedia is a desktop or living room experience, because the apparatus is so clunky. This will change dramatically with small, bright, thin, high-resolution displays. — 1995]

293
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We came to them.

294
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I looked forward to it every year.

295
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It was the party that Ricky Wurman never had

296
00:13:01,280 --> 00:13:04,189
in the sense that he invited many of his old friends,

297
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including myself.

298
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And then something for me changed

299
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pretty profoundly.

300
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I became more involved with computers and learning

301
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and influenced by Seymour,

302
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but particularly looking at learning

303
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as something that is best approximated

304
00:13:22,649 --> 00:13:24,403
by computer programming.

305
00:13:24,403 --> 00:13:26,417
When you write a computer program,

306
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you've got to not just list things out

307
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and sort of take an algorithm

308
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and translate it into a set of instructions,

309
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but when there's a bug, and all programs have bugs,

310
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you've got to de-bug it.

311
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You've got to go in, change it,

312
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and then re-execute,

313
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and you iterate,

314
00:13:43,624 --> 00:13:46,531
and that iteration is really

315
00:13:46,531 --> 00:13:49,434
a very, very good approximation of learning.

316
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So that led to my own work with Seymour

317
00:13:53,101 --> 00:13:55,459
in places like Cambodia

318
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and the starting of One Laptop per Child.

319
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Enough TED Talks on One Laptop per Child,

320
00:14:01,177 --> 00:14:02,938
so I'll go through it very fast,

321
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but it did give us the chance

322
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to do something at a relatively large scale

323
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in the area of learning, development and computing.

324
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Very few people know that One Laptop per Child

325
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was a $1 billion project,

326
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and it was, at least over the seven years I ran it,

327
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but even more important, the World Bank

328
00:14:24,607 --> 00:14:27,722
contributed zero, USAID zero.

329
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It was mostly the countries
using their own treasuries,

330
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which is very interesting,

331
00:14:33,480 --> 00:14:34,836
at least to me it was very interesting

332
00:14:34,836 --> 00:14:37,980
in terms of what I plan to do next.

333
00:14:37,980 --> 00:14:41,005
So these are the various places it happened.

334
00:14:41,005 --> 00:14:43,907
I then tried an experiment,

335
00:14:43,907 --> 00:14:48,188
and the experiment happened in Ethiopia.

336
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And here's the experiment.

337
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The experiment is,

338
00:14:52,461 --> 00:14:56,241
can learning happen where there are no schools.

339
00:14:56,241 --> 00:14:58,771
And we dropped off tablets

340
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with no instructions

341
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and let the children figure it out.

342
00:15:04,287 --> 00:15:07,934
And in a short period of time,

343
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they not only

344
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turned them on and were using 50 apps per child

345
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within five days,

346
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they were singing "ABC" songs within two weeks,

347
00:15:18,140 --> 00:15:22,033
but they hacked Android within six months.

348
00:15:22,033 --> 00:15:25,551
And so that seemed sufficiently interesting.

349
00:15:25,551 --> 00:15:28,110
This is perhaps the best picture I have.

350
00:15:28,110 --> 00:15:32,261
The kid on your right

351
00:15:32,261 --> 00:15:34,736
has sort of nominated himself as teacher.

352
00:15:34,736 --> 00:15:37,256
Look at the kid on the left, and so on.

353
00:15:37,256 --> 00:15:40,406
There are no adults involved in this at all.

354
00:15:40,406 --> 00:15:41,830
So I said, well can we do this

355
00:15:41,830 --> 00:15:43,427
at a larger scale?

356
00:15:43,427 --> 00:15:45,908
And what is it that's missing?

357
00:15:45,908 --> 00:15:48,177
The kids are giving a press conference at this point,

358
00:15:48,177 --> 00:15:50,862
and sort of writing in the dirt.

359
00:15:50,862 --> 00:15:54,307
And the answer is, what is missing?

360
00:15:54,307 --> 00:15:56,843
And I'm going to skip over my prediction, actually,

361
00:15:56,843 --> 00:15:58,371
because I'm running out of time,

362
00:15:58,371 --> 00:16:02,339
and here's the question, is what's going to happen?

363
00:16:02,339 --> 00:16:03,826
I think the challenge

364
00:16:03,826 --> 00:16:06,454
is to connect the last billion people,

365
00:16:06,454 --> 00:16:09,105
and connecting the last billion

366
00:16:09,105 --> 00:16:12,502
is very different than connecting the next billion,

367
00:16:12,502 --> 00:16:13,896
and the reason it's different

368
00:16:13,896 --> 00:16:15,760
is that the next billion

369
00:16:15,760 --> 00:16:17,710
are sort of low-hanging fruit,

370
00:16:17,710 --> 00:16:21,077
but the last billion are rural.

371
00:16:21,077 --> 00:16:24,829
Being rural and being poor

372
00:16:24,829 --> 00:16:25,961
are very different.

373
00:16:25,961 --> 00:16:29,594
Poverty tends to be created by our society,

374
00:16:29,594 --> 00:16:35,044
and the people in that community are not poor

375
00:16:35,044 --> 00:16:36,953
in the same way at all.

376
00:16:36,953 --> 00:16:38,358
They may be primitive,

377
00:16:38,358 --> 00:16:42,402
but the way to approach it and to connect them,

378
00:16:42,402 --> 00:16:44,933
the history of One Laptop per Child,

379
00:16:44,933 --> 00:16:48,589
and the experiment in Ethiopia,

380
00:16:48,589 --> 00:16:51,864
lead me to believe that we can in fact

381
00:16:51,864 --> 00:16:54,665
do this in a very short period of time.

382
00:16:54,665 --> 00:16:56,506
And so my plan,

383
00:16:56,506 --> 00:16:58,740
and unfortunately I haven't been able

384
00:16:58,740 --> 00:17:01,608
to get my partners at this point

385
00:17:01,608 --> 00:17:02,899
to let me announce them,

386
00:17:02,899 --> 00:17:07,806
but is to do this with a stationary satellite.

387
00:17:07,806 --> 00:17:10,265
There are many reasons

388
00:17:10,265 --> 00:17:14,780
that stationary satellites aren't the best things,

389
00:17:14,780 --> 00:17:17,717
but there are a lot of reasons why they are,

390
00:17:17,717 --> 00:17:20,812
and for two billion dollars,

391
00:17:20,812 --> 00:17:24,496
you can connect a lot more than 100 million people,

392
00:17:24,496 --> 00:17:27,157
but the reason I picked two,

393
00:17:27,157 --> 00:17:30,540
and I will leave this as my last slide,

394
00:17:30,540 --> 00:17:32,324
is two billion dollars

395
00:17:32,324 --> 00:17:35,243
is what we were spending

396
00:17:35,243 --> 00:17:37,336
in Afghanistan

397
00:17:37,336 --> 00:17:39,248
every week.

398
00:17:39,248 --> 00:17:42,555
So surely if we can connect

399
00:17:42,555 --> 00:17:45,255
Africa and the last billion people

400
00:17:45,255 --> 00:17:46,809
for numbers like that,

401
00:17:46,809 --> 00:17:48,122
we should be doing it.

402
00:17:48,122 --> 00:17:50,419
Thank you very much.

403
00:17:50,419 --> 00:17:53,948
(Applause)

404
00:17:53,948 --> 00:17:58,278
Chris Anderson: Stay up there. Stay up there.

405
00:17:58,278 --> 00:18:00,308
NN: You're going to give me extra time?

406
00:18:00,308 --> 00:18:02,670
CA: No. That was wickedly clever, wickedly clever.

407
00:18:02,670 --> 00:18:04,535
You gamed it beautifully.

408
00:18:04,535 --> 00:18:07,165
Nicholas, what is your prediction?

409
00:18:07,165 --> 00:18:09,191
(Laughter)

410
00:18:09,191 --> 00:18:11,627
NN: Thank you for asking.

411
00:18:11,627 --> 00:18:14,400
I'll tell you what my prediction is,

412
00:18:14,400 --> 00:18:17,100
and my prediction, and this is a prediction,

413
00:18:17,100 --> 00:18:19,762
because it'll be 30 years. I won't be here.

414
00:18:19,762 --> 00:18:24,490
But one of the things about learning how to read,

415
00:18:24,490 --> 00:18:27,339
we have been doing a lot of consuming

416
00:18:27,339 --> 00:18:29,624
of information going through our eyes,

417
00:18:29,624 --> 00:18:32,700
and so that may be a very inefficient channel.

418
00:18:32,700 --> 00:18:37,785
So my prediction is that we are 
going to ingest information

419
00:18:37,785 --> 00:18:40,982
You're going to swallow a pill and know English.

420
00:18:40,982 --> 00:18:43,674
You're going to swallow a
pill and know Shakespeare.

421
00:18:43,674 --> 00:18:46,283
And the way to do it is through the bloodstream.

422
00:18:46,283 --> 00:18:48,140
So once it's in your bloodstream,

423
00:18:48,140 --> 00:18:50,358
it basically goes through it and gets into the brain,

424
00:18:50,358 --> 00:18:52,540
and when it knows that it's in the brain

425
00:18:52,540 --> 00:18:53,862
in the different pieces,

426
00:18:53,862 --> 00:18:56,487
it deposits it in the right places.

427
00:18:56,487 --> 00:18:57,819
So it's ingesting.

428
00:18:57,819 --> 00:19:00,339
CA: Have you been hanging out
with Ray Kurzweil by any chance?

429
00:19:00,339 --> 00:19:03,552
NN: No, but I've been hanging
around with Ed Boyden

430
00:19:03,552 --> 00:19:05,397
and hanging around with one of the speakers

431
00:19:05,397 --> 00:19:07,210
who is here, Hugh Herr,

432
00:19:07,210 --> 00:19:09,107
and there are a number of people.

433
00:19:09,107 --> 00:19:10,504
This isn't quite as far-fetched,

434
00:19:10,504 --> 00:19:13,449
so 30 years from now.

435
00:19:13,449 --> 00:19:15,191
CA: We will check it out.

436
00:19:15,191 --> 00:19:17,493
We're going to be back and we're going
to play this clip 30 years from now,

437
00:19:17,493 --> 00:19:20,524
and then all eat the red pill.

438
00:19:20,524 --> 00:19:22,709
Well thank you for that.

439
00:19:22,709 --> 00:19:24,153
Nicholas Negroponte.

440
00:19:24,153 --> 00:19:25,501
NN: Thank you.

441
00:19:25,501 --> 00:19:26,315
(Applause)