0:00:00.543,0:00:03.286
On March 10, 2011,

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I was in Cambridge at the MIT Media Lab

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meeting with faculty, students and staff,

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and we were trying to figure out whether

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I should be the next director.

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That night, at midnight,

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a magnitude 9 earthquake

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hit off of the Pacific coast of Japan.

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My wife and family were in Japan,

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and as the news started to come in,

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I was panicking.

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I was looking at the news streams

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and listening to the press conferences

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of the government officials

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and the Tokyo Power Company,

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and hearing about this explosion

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at the nuclear reactors

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and this cloud of fallout

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that was headed towards our house

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which was only about 200 kilometers away.

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And the people on TV weren't telling us

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anything that we wanted to hear.

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I wanted to know what was going on with the reactor,

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what was going on with the radiation,

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whether my family was in danger.

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So I did what instinctively felt like the right thing,

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which was to go onto the Internet

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and try to figure out

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if I could take matters into my own hands.

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On the Net, I found there were a lot of other people

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like me trying to figure out what was going on,

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and together we sort of loosely formed a group

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and we called it Safecast,

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and we decided we were going to try

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to measure the radiation

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and get the data out to everybody else,

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because it was clear that the government

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wasn't going to be doing this for us.

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Three years later,

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we have 16 million data points,

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we have designed our own Geiger counters

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that you can download the designs

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and plug it into the network.

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We have an app that shows you

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most of the radiation in Japan[br]and other parts of the world.

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We are arguably one of the most successful

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citizen science projects in the world,

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and we have created

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the largest open dataset of radiation measurements.

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And the interesting thing here

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is how did — (Applause) — Thank you.

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How did a bunch of amateurs

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who really didn't know what we were doing

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somehow come together

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and do what NGOs and the government

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were completely incapable of doing?

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And I would suggest that this has something to do

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with the Internet. It's not a fluke.

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It wasn't luck, and it wasn't because it was us.

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It helped that it was an event

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that pulled everybody together,

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but it was a new way of doing things

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that was enabled by the Internet

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and a lot of the other things that were going on,

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and I want to talk a little bit about

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what those new principles are.

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So remember before the Internet? (Laughter)

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I call this B.I. Okay?

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So, in B.I., life was simple.

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Things were Euclidian, Newtonian,

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somewhat predictable.

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People actually tried to predict the future,

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even the economists.

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And then the Internet happened,

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and the world became extremely complex,

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extremely low-cost, extremely fast,

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and those Newtonian laws

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that we so dearly cherished

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turned out to be just local ordinances,

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and what we found was that in this

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completely unpredictable world

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that most of the people who were surviving

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were working with sort of a different set of principles,

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and I want to talk a little bit about that.

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Before the Internet, if you remember,

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when we tried to create services,

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what you would do is you'd create

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the hardware layer and the[br]network layer and the software

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and it would cost millions of dollars

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to do anything that was substantial.

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So when it costs millions of dollars[br]to do something substantial,

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what you would do is you'd get an MBA

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who would write a plan

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and get the money

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from V.C.s or big companies,

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and then you'd hire the designers and the engineers,

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and they'd build the thing.

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This is the Before Internet, B.I., innovation model.

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What happened after the Internet was

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the cost of innovation went down so much

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because the cost of collaboration,[br]the cost of distribution,

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the cost of communication, and Moore's Law

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made it so that the cost of trying a new thing

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became nearly zero,

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and so you would have Google, Facebook, Yahoo,

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students that didn't have permission —

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permissionless innovation —

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didn't have permission, didn't have PowerPoints,

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they just built the thing,

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then they raised the money,

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and then they sort of figured out a business plan

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and maybe later on they hired some MBAs.

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So the Internet caused innovation,

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at least in software and services,

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to go from an MBA-driven innovation model

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to a designer-engineer-driven innovation model,

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and it pushed innovation to the edges,

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to the dorm rooms, to the startups,

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away from the large institutions,

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the stodgy old institutions that had the power

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and the money and the authority.

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And we all know this. We all know[br]this happened on the Internet.

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It turns out it's happening in other things, too.

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Let me give you some examples.

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So at the Media Lab, we don't just do hardware.

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We do all kinds of things.

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We do biology, we do hardware,

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and Nicholas Negroponte[br]famously said, "Demo or die,"

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as opposed to "Publish or perish,"

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which was the traditional academic way of thinking.

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And he often said, the demo only has to work once,

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because the primary mode of us impacting the world

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was through large companies

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being inspired by us

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and creating products like[br]the Kindle or Lego Mindstorms.

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But today, with the ability

0:05:04.190,0:05:06.499
to deploy things into the real world at such low cost,

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I'm changing the motto now,

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and this is the official public statement.

0:05:10.462,0:05:12.959
I'm officially saying, "Deploy or die."

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You have to get the stuff into the real world

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for it to really count,

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and sometimes it will be large companies,

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and Nicholas can talk about satellites.

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(Applause)

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Thank you.

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But we should be getting out there ourselves

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and not depending on large[br]institutions to do it for us.

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So last year, we sent a bunch[br]of students to Shenzhen,

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and they sat on the factory floors

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with the innovators in Shenzhen, and it was amazing.

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What was happening there

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was you would have these manufacturing devices,

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and they weren't making prototypes or PowerPoints.

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They were fiddling with the manufacturing equipment

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and innovating right on the[br]manufacturing equipment.

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The factory was in the designer,

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and the designer was literally in the factory.

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And so what you would do is,

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you'd go down to the stalls

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and you would see these cell phones.

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So instead of starting little websites

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like the kids in Palo Alto do,

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the kids in Shenzhen make new cell phones.

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They make new cell phones like kids in Palo Alto

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make websites,

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and so there's a rainforest

0:06:08.478,0:06:10.034
of innovation going on in the cell phone.

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What they do is, they make a cell phone,

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go down to the stall, they sell some,

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they look at the other kids' stuff, go up,

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make a couple thousand more, go down.

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Doesn't this sound like a software thing?

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It sounds like agile software development,

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A/B testing and iteration,

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and what we thought you could only do with software

0:06:27.423,0:06:29.693
kids in Shenzhen are doing this in hardware.

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My next fellow, I hope, is going to be

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one of these innovators from Shenzhen.

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And so what you see is

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that is pushing innovation to the edges.

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We talk about 3D printers and stuff like that,

0:06:38.384,0:06:40.375
and that's great, but this is Limor.

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She is one of our favorite graduates,

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and she is standing in front of a Samsung

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Techwin Pick and Place Machine.

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This thing can put 23,000 components per hour

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onto an electronics board.

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This is a factory in a box.

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So what used to take a factory full of workers

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working by hand

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in this little box in New York,

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she's able to have effectively —

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She doesn't actually have to go to Shenzhen

0:07:02.192,0:07:03.436
to do this manufacturing.

0:07:03.436,0:07:05.697
She can buy this box and she can manufacture it.

0:07:05.697,0:07:07.940
So manufacturing, the cost of innovation,

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the cost of prototyping, distribution,[br]manufacturing, hardware,

0:07:10.630,0:07:12.093
is getting so low

0:07:12.093,0:07:14.410
that innovation is being pushed to the edges

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and students and startups are being able to build it.

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This is a recent thing, but this will happen

0:07:18.716,0:07:20.199
and this will change

0:07:20.199,0:07:22.624
just like it did with software.

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Sorona is a DuPont process

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that uses a genetically engineered microbe

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to turn corn sugar into polyester.

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It's 30 percent more efficient[br]than the fossil fuel method,

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and it's much better for the environment.

0:07:38.977,0:07:40.382
Genetic engineering and bioengineering

0:07:40.382,0:07:41.913
are creating a whole bunch

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of great new opportunities

0:07:43.671,0:07:46.500
for chemistry, for computation, for memory.

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We will probably be doing a lot,[br]obviously doing health things,

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but we will probably be growing chairs

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and buildings soon.

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The problem is, Sorona costs[br]about 400 million dollars

0:07:55.704,0:07:57.085
and took seven years to build.

0:07:57.085,0:08:00.164
It kind of reminds you of the old mainframe days.

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The thing is, the cost of innovation

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in bioengineering is also going down.

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This is desktop gene sequencer.

0:08:06.211,0:08:09.765
It used to cost millions and millions[br]of dollars to sequence genes.

0:08:09.765,0:08:11.509
Now you can do it on a desktop like this,

0:08:11.509,0:08:13.602
and kids can do this in dorm rooms.

0:08:13.602,0:08:16.290
This is Gen9 gene assembler,

0:08:16.290,0:08:18.369
and so right now when you try to print a gene,

0:08:18.369,0:08:19.637
what you do is somebody in a factory

0:08:19.637,0:08:21.577
with pipettes puts the thing together by hand,

0:08:21.577,0:08:23.928
you have one error per 100 base pairs,

0:08:23.928,0:08:26.504
and it takes a long time and costs a lot of money.

0:08:26.504,0:08:27.890
This new device

0:08:27.890,0:08:29.564
assembles genes on a chip,

0:08:29.564,0:08:31.713
and instead of one error per 100 base pairs,

0:08:31.713,0:08:33.839
it's one error per 10,000 base pairs.

0:08:33.839,0:08:36.584
In this lab, we will have the world's capacity

0:08:36.584,0:08:38.687
of gene printing within a year,

0:08:38.687,0:08:41.299
200 million base pairs a year.

0:08:41.299,0:08:43.862
This is kind of like when we went

0:08:43.862,0:08:46.123
from transistor radios wrapped by hand

0:08:46.123,0:08:47.394
to the Pentium.

0:08:47.394,0:08:49.790
This is going to become the[br]Pentium of bioengineering,

0:08:49.790,0:08:51.826
pushing bioengineering into the hands

0:08:51.826,0:08:54.427
of dorm rooms and startup companies.

0:08:54.427,0:08:57.200
So it's happening in software and in hardware

0:08:57.200,0:08:58.163
and bioengineering,

0:08:58.163,0:09:01.444
and so this is a fundamental new[br]way of thinking about innovation.

0:09:01.444,0:09:04.121
It's a bottom-up innovation, it's democratic,

0:09:04.121,0:09:06.325
it's chaotic, it's hard to control.

0:09:06.325,0:09:08.632
It's not bad, but it's very different,

0:09:08.632,0:09:10.599
and I think that the traditional rules that we have

0:09:10.599,0:09:12.671
for institutions don't work anymore,

0:09:12.671,0:09:14.350
and most of us here

0:09:14.350,0:09:17.433
operate with a different set of principles.

0:09:17.433,0:09:20.269
One of my favorite principles is the power of pull,

0:09:20.269,0:09:22.560
which is the idea of pulling resources

0:09:22.560,0:09:24.326
from the network as you need them

0:09:24.326,0:09:26.171
rather than stocking them in the center

0:09:26.171,0:09:27.756
and controlling everything.

0:09:27.756,0:09:30.520
So in the case of the Safecast story,

0:09:30.520,0:09:32.362
I didn't know anything when[br]the earthquake happened,

0:09:32.362,0:09:33.990
but I was able to find Sean

0:09:33.990,0:09:36.186
who was the hackerspace community organizer,

0:09:36.186,0:09:37.972
and Peter, the analog hardware hacker

0:09:37.972,0:09:39.688
who made our first Geiger counter,

0:09:39.688,0:09:41.686
and Dan, who built the Three Mile Island

0:09:41.686,0:09:45.020
monitoring system after the[br]Three Mile Island meltdown.

0:09:45.020,0:09:47.406
And these people I wouldn't have been able to find

0:09:47.406,0:09:49.840
beforehand and probably were better

0:09:49.840,0:09:52.967
that I found them just in time from the network.

0:09:52.967,0:09:54.834
I'm a three-time college dropout,

0:09:54.834,0:09:56.507
so learning over education

0:09:56.507,0:09:57.932
is very near and dear to my heart,

0:09:57.932,0:10:00.456
but to me, education is what people do to you

0:10:00.456,0:10:03.455
and learning is what you do to yourself.

0:10:03.455,0:10:07.231
(Applause)

0:10:07.231,0:10:08.990
And it feels like, and I'm biased,

0:10:08.990,0:10:11.787
it feels like they're trying to make you memorize

0:10:11.787,0:10:14.901
the whole encyclopedia before[br]they let you go out and play,

0:10:14.901,0:10:18.998
and to me, I've got Wikipedia on my cell phone,

0:10:18.998,0:10:20.701
and it feels like they assume

0:10:20.701,0:10:22.488
you're going to be on top of some mountain

0:10:22.488,0:10:24.949
all by yourself with a number 2 pencil

0:10:24.949,0:10:26.332
trying to figure out what to do

0:10:26.332,0:10:28.448
when in fact you're always going to be connected,

0:10:28.448,0:10:30.093
you're always going to have friends,

0:10:30.093,0:10:32.052
and you can pull Wikipedia[br]up whenever you need it,

0:10:32.052,0:10:35.500
and what you need to learn is how to learn.

0:10:35.500,0:10:38.144
In the case of Safecast, a bunch of amateurs

0:10:38.144,0:10:39.742
when we started three years ago,

0:10:39.742,0:10:42.250
I would argue that we probably as a group

0:10:42.250,0:10:44.666
know more than any other organization

0:10:44.666,0:10:47.875
about how to collect data and publish data

0:10:47.875,0:10:50.647
and do citizen science.

0:10:50.647,0:10:51.767
Compass over maps.

0:10:51.767,0:10:55.492
So this one, the idea is that the cost of writing a plan

0:10:55.492,0:10:58.595
or mapping something is getting so expensive

0:10:58.595,0:11:01.768
and it's not very accurate or useful.

0:11:01.768,0:11:04.880
So in the Safecast story, we[br]knew we needed to collect data,

0:11:04.880,0:11:07.303
we knew we wanted to publish the data,

0:11:07.303,0:11:10.192
and instead of trying to come up with the exact plan,

0:11:10.192,0:11:12.600
we first said, oh, let's get Geiger counters.

0:11:12.600,0:11:14.366
Oh, they've run out.

0:11:14.366,0:11:16.369
Let's build them. There aren't enough sensors.

0:11:16.369,0:11:18.596
Okay, then we can make a mobile Geiger counter.

0:11:18.596,0:11:20.643
We can drive around. We can get volunteers.

0:11:20.643,0:11:22.522
We don't have enough money. Let's Kickstarter it.

0:11:22.522,0:11:24.513
We could not have planned this whole thing,

0:11:24.513,0:11:26.257
but by having a very strong compass,

0:11:26.257,0:11:27.692
we eventually got to where we were going,

0:11:27.692,0:11:30.110
and to me it's very similar to[br]agile software development,

0:11:30.110,0:11:33.468
but this idea of compasses is very important.

0:11:33.468,0:11:35.409
So I think the good news is

0:11:35.409,0:11:38.910
that even though the world is extremely complex,

0:11:38.920,0:11:41.302
what you need to do is very simple.

0:11:41.302,0:11:44.000
I think it's about stopping this notion

0:11:44.000,0:11:45.572
that you need to plan everything,

0:11:45.572,0:11:46.664
you need to stock everything,

0:11:46.664,0:11:48.134
and you need to be so prepared,

0:11:48.134,0:11:51.128
and focus on being connected,

0:11:51.128,0:11:52.979
always learning,

0:11:52.979,0:11:54.840
fully aware,

0:11:54.840,0:11:56.620
and super present.

0:11:56.620,0:11:59.566
So I don't like the word "futurist."

0:11:59.566,0:12:05.181
I think we should be now-ists,

0:12:05.181,0:12:07.227
like we are right now.

0:12:07.227,0:12:09.070
Thank you.

0:12:09.070,0:12:13.049
(Applause)