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[telephone rings]
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00:00:09,426 --> 00:00:11,594
-[woman] 9-1-1, emergency?
-[telephone rings]
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00:00:11,678 --> 00:00:13,346
[second woman]
911. What's your emergency?
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00:00:13,430 --> 00:00:16,516
-[man] 9-1-1. What's your emergency?
-[second woman] 9-1-1.
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[Karlie Kloss] On April 9, 2014,
9-1-1 service suddenly stopped
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for millions of people
across the United States.
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It was down for over six hours.
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00:00:30,280 --> 00:00:33,324
More than 6,000 emergency calls
couldn't get through.
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The government traced the problem
to a computer in a call-routing facility
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in Englewood, Colorado.
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It was a simple coding mistake.
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The people in charge
of coding that computer
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chose to do it with an upper limit
for the number of calls it could log,
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a limit the coders thought
the computer would never hit.
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But that night in 2014, it did.
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The computer
followed its instructions perfectly.
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It hit the limit
and stopped routing calls.
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The problem wasn't the computer,
and it wasn't a bug in the code.
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It was the coding,
the decision-making process
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by which people communicate
with the computer.
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This kind of power
comes with great ethical responsibility.
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There's nothing like doing it.
There's nothing that substitutes for it.
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You know, much the same ways
that builders of a city
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determine how your life
is lived in the city,
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I-I think code
controls how we live online,
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which basically is how we live.
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Not just when we go on the Internet,
but when we contact emergency services...
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or go to the doctor or get in a car.
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We're all so close to code every day.
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Yet only around
a third of one percent of us
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know how to write it.
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To the overwhelming majority,
it's a black box.
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But it doesn't have to be.
So, how does coding really work?
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And what new world
are we building with it?
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[man] The computer.
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An ingenious collection
of electronic hardware
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was created by man.
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[second man] It is not that we do not have
adequate machines to solve our problems,
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but rather we lack adequate descriptions
of how to solve our problems.
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[woman] When someone says coding,
you think it's really, really hard.
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[man] It's very important
to really remember
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everything you use on your computer
was created by some human being.
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Let's say an alien came, and you're like,
"Okay, what's the importance of code?
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What is it?" I'd say, "Well, you know,
we live on this sort of physical earth,
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and about 50 years ago,
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a small group of people
started building another planet.
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But it wasn't physical, virtual planet.
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Look around the street. You see
all the people walking down the street
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with their head bent down
and staring at their phone?
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They're actually in that other world.
So, that's what code is.
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It's the building blocks
of that other world."
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This loom is the ancestor of every
computer and smartphone on Earth.
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00:03:04,767 --> 00:03:09,314
It was invented in 1804,
and the big innovation was these cards.
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The holes in each card
allowed only certain pins to pass through.
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With thousands of holes
on hundreds of cards,
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00:03:16,446 --> 00:03:19,699
weavers could do more complex patterns
than they could before.
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Elaborate shawls
became all the rage in Europe.
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And woven designs could be so intricate,
they looked like drawings,
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like this one of the loom's inventor.
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Before these looms, individual strings
had to be selected by hand
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00:03:33,504 --> 00:03:34,839
by "draw boys."
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00:03:34,923 --> 00:03:38,968
Math back then was done by hand, too,
by so-called "computers."
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The first computers were people.
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And the best machines we had to help us
could only do one type of math problem,
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like the abacus
for adding and subtracting.
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00:03:49,020 --> 00:03:51,022
British mathematician Charles Babbage
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00:03:51,105 --> 00:03:54,692
wanted a machine that could do
any math problem you chose for it to do
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or rather "programmed" it to do.
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He proposed a machine
he called "The Analytical Engine."
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00:04:01,241 --> 00:04:04,911
Babbage's idea
would earn him a place in history.
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00:04:04,994 --> 00:04:10,500
Computers were invented first by Babbage,
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a very eccentric British inventor.
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Babbage had inspiration
for how it would work.
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He kept a copy of this picture
hanging in his house.
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00:04:20,176 --> 00:04:23,221
Babbage's Analytical Engine,
like Jacquard's loom,
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00:04:23,304 --> 00:04:25,515
had physical parts--hardware.
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And also like the loom,
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you could give the hardware instructions
in the form of cards punched with holes.
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00:04:31,604 --> 00:04:32,981
The holes let pins in,
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00:04:33,064 --> 00:04:36,025
and the absence of holes
forced other pins backwards,
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00:04:36,109 --> 00:04:39,153
setting off a chain
of mechanical calculations.
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00:04:39,737 --> 00:04:42,532
The cards with their different holes,
that's software.
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00:04:43,658 --> 00:04:45,952
Babbage never finished
his Analytical Engine,
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00:04:46,035 --> 00:04:48,037
but a young woman working with him
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00:04:48,121 --> 00:04:52,542
saw its world-changing potential
way beyond just math.
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00:04:52,625 --> 00:04:55,837
Ada Byron, Countess of Lovelace, wrote,
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00:04:55,920 --> 00:04:58,047
"The bounds of arithmetic were outstepped
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the moment the idea
of applying the cards had occurred."
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She saw what Jacquard saw--
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00:05:04,304 --> 00:05:06,931
the holes could represent
more than just numbers.
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00:05:07,015 --> 00:05:09,267
They could be patterns, music...
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00:05:10,560 --> 00:05:12,645
or entire sentences.
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You can think of it
kind of as Morse code.
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00:05:15,231 --> 00:05:17,358
Each letter in the Morse-code alphabet
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is expressed as a set
of only two signals--
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[short beep] or [long beep].
It's binary.
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00:05:23,197 --> 00:05:26,784
And with just those beeps,
we can say anything,
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00:05:26,868 --> 00:05:30,788
like this distress call
sent out by the Titanic in 1912.
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00:05:31,622 --> 00:05:34,584
SOS doesn't stand for anything.
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00:05:34,667 --> 00:05:37,879
It's just incredibly simple
to send in Morse code.
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00:05:37,962 --> 00:05:40,798
[Andy] You can equally well think
of every letter
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could be expressed as a combination
of zeros and ones.
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[Kloss] Look familiar?
This is binary code.
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And it's how we bridge the gap
between machines and human language.
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Each one or zero
is a binary digit or "bit."
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These are the atoms of modern computing.
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You may know them by another name--
eight bits is a byte.
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So, you know that picture on your computer
that's 1.1 megabytes?
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That's 8,800,000 ones and zeros.
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Like Morse code's dots and dashes
are just a way to write down
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[long beep] and [short beep],
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binary code's ones and zeros
are just the way we write down
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what's really happening
in a modern computer--
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charge or no charge.
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This is a simple electrical circuit.
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Imagine millions of these
all working together.
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That's a computer today.
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On an electric circuit, this is a bit.
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Is the light bulb off? Zero.
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On? One.
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Computers only understand electricity,
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so everything coders do with computers
is, in the end,
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just a series of on-or-off charges.
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It all works because,
strung together in just the right way,
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those charges can represent logic.
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[man] Basically, logic is
a predictable series of facts or events,
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such as closing this switch...
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and this one to ring the bell.
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[bell rings]
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In fact, computer people call this
a logic AND circuit.
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[Kloss] Or a logic gate.
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Let's see if I can do this
without burning a hole through this table.
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In an AND gate, both circuits
need to be closed for the light to go on.
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And there are OR gates,
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where the light goes on
if just one of the circuits is closed.
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You can put this another way.
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If one of these circuits is closed,
then turn on the light.
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That kind of if/then statement,
that's an algorithm.
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In pop culture today, the word "algorithm"
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causes lots of confusion.
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We've seen this before,
uh, where the algorithms go haywire.
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The way algorithms work
is something of a mystery to most people.
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What the heck is an algorithm, anyway?
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[Kloss] But an algorithm
is really just a set of directions.
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Imagine walking to the store.
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You could take a left
and then take a right.
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Or you could just take a right,
then turn left.
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00:08:03,024 --> 00:08:05,026
Or you could also take four lefts,
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run around the park, cross a highway,
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and then take four rights again.
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Just like there are different directions
to get to the same place,
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in coding, there can be
many different algorithms
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to solve the same problem.
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The goal is to find
the most elegant, efficient one.
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Beautiful code doesn't repeat itself.
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It's very elegant. It's powerful.
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Computers running algorithms
just did what we told them to do,
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but so much faster,
which made people so much more powerful.
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When scientists first began to develop
the fusion bomb,
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they primarily used human computers.
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But then they turned to this one--
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the ENIAC computer ran
thermonuclear calculations for six weeks.
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Its results contributed directly to this--
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the first successful test in 1952
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of a bomb hundreds of times more powerful
than the atomic fission bombs
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dropped on Hiroshima and Nagasaki
during World War II.
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The power to code
amplified people's ability to do
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what they chose to do.
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But in the 1940s,
it was still a lot of work.
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[Andy] Writing programs in zeros and ones
clearly doesn't scale.
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[Kloss] People wanted more
of the power coding gave,
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but they wanted an easier way to code.
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The story of coding since then
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has been the story of making code
closer and closer to human language
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by inventing what nearly all coders today
actually use--programming languages.
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Compared to ones and zeros,
these languages are pretty abstract.
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Abstraction's a word
that's tough for people.
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More abstract languages
boil down to the same ones and zeros.
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00:09:45,835 --> 00:09:48,671
We've just found better ways
to organize them.
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You can think of it in terms of biology.
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Humans are incredibly complex,
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but 99% of our bodies
are made up of only six elements.
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[Alan] And you can
work your way up to large molecules.
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Between that layer of organization
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00:10:02,310 --> 00:10:04,645
and the one that is
the simplest living thing
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is actually a bit of a jump.
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[Kloss] And humans have brains
which do things so advanced,
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it's hard to believe
they're still made of the same stuff.
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Computers actually are rather like that,
but are much simpler.
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So that is the good news.
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The story of coding
is the story of moving this box up,
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moving away from binary
to give ourselves easier, faster,
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00:10:26,667 --> 00:10:28,961
more powerful ways to code
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00:10:29,045 --> 00:10:32,298
without having to deal with
or really even understand
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the binary and logic gates beneath.
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That's what allows coders to make
the products we're all familiar with.
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00:10:39,263 --> 00:10:41,349
The first step to get there was...
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00:10:41,432 --> 00:10:46,103
[Andy] "Assembly language,"
which is much easier to read and write,
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00:10:46,187 --> 00:10:49,774
where you say
instead of 0-1-0-0-0-1-1-1,
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let's call it "add,"
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00:10:51,651 --> 00:10:55,363
and then have a program
called the assembler
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00:10:55,446 --> 00:10:59,367
translate the letters A-D-D
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to the appropriate
equivalent zeros and ones.
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00:11:03,537 --> 00:11:07,500
[Kloss] At this level, binary
is organized into letters and numbers,
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00:11:07,583 --> 00:11:10,753
just like atoms
are organized into molecules.
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00:11:10,836 --> 00:11:15,716
But coding in assembly language
still wasn't exactly easy,
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00:11:15,800 --> 00:11:19,970
because all these computers
used different assembly languages.
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00:11:20,054 --> 00:11:24,975
If you wrote a program for one computer,
it wouldn't work on any of the others.
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00:11:25,059 --> 00:11:27,144
Very quickly,
people started thinking about,
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00:11:27,228 --> 00:11:29,397
"Well, what we really
want to give the computer
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00:11:29,480 --> 00:11:33,067
are things in terms
that we actually use every day."
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00:11:33,150 --> 00:11:35,778
You have programming languages
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00:11:35,861 --> 00:11:39,782
that we built using the assembly language,
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00:11:39,865 --> 00:11:42,868
and then from those programming languages,
we build more programming languages.
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00:11:42,952 --> 00:11:44,912
You've probably heard their names.
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00:11:44,995 --> 00:11:45,871
-LISP.
-BASIC.
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00:11:45,955 --> 00:11:47,164
-Java.
-C++.
218
00:11:47,248 --> 00:11:48,999
-[man] Python 3.
-HTML 5.
219
00:11:49,083 --> 00:11:51,001
PEARL. PHP. A little bit of C.
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00:11:51,085 --> 00:11:53,629
Just like how spoken languages
are different ways
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00:11:53,713 --> 00:11:57,174
of expressing the same idea
to other people,
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00:11:57,258 --> 00:11:58,467
programming languages
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00:11:58,551 --> 00:12:02,221
are just different ways of expressing
the same idea to computers.
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00:12:02,304 --> 00:12:04,807
[Andy] We have more than one
high-level language,
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00:12:04,890 --> 00:12:06,767
because, first of all,
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00:12:06,851 --> 00:12:10,604
different languages
address different needs.
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00:12:10,688 --> 00:12:12,148
[Kloss] Take a look at these two.
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00:12:12,231 --> 00:12:15,860
This one, COBOL,
was created in the late 1950s
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00:12:15,943 --> 00:12:19,113
to make it easier for businesses
to use code.
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00:12:19,196 --> 00:12:21,115
It looks a lot like English,
231
00:12:21,198 --> 00:12:25,578
except if every conversation
ended with "STOP RUN."
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00:12:26,454 --> 00:12:30,291
This one, CPL, was developed in the 1960s
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00:12:30,374 --> 00:12:33,085
and included more scientific computing.
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00:12:33,169 --> 00:12:35,504
It's like biological evolution.
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00:12:35,588 --> 00:12:38,591
As organisms get more complex,
they develop features
236
00:12:38,674 --> 00:12:41,886
that make them better adapted
to their specific environments.
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00:12:41,969 --> 00:12:46,390
And, frankly, it's also a matter of taste.
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00:12:46,474 --> 00:12:50,478
People like different tools
for expressing themselves.
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00:12:50,561 --> 00:12:53,731
For example, the language C++.
240
00:12:53,814 --> 00:12:56,233
Elon Musk... n-not a fan.
241
00:12:56,317 --> 00:12:57,860
You could make one up.
242
00:12:57,943 --> 00:13:02,823
This is a real high-level language
made entirely of the word "moo."
243
00:13:02,907 --> 00:13:05,159
Seriously. It's called COW.
244
00:13:05,242 --> 00:13:09,121
This one is made of
Arnold Schwarzenegger movie quotes.
245
00:13:09,205 --> 00:13:13,292
Every time I think,
"Okay, we must be done by now,"
246
00:13:13,375 --> 00:13:15,753
somebody else comes up with a new language
247
00:13:15,836 --> 00:13:19,965
and it develops a group of devotees.
248
00:13:20,049 --> 00:13:24,845
So I don't see any end in sight
to the invention of new languages.
249
00:13:25,429 --> 00:13:29,266
And all of these languages
are still based around logic.
250
00:13:29,350 --> 00:13:32,561
For example,
a coder at Netflix could say,
251
00:13:32,645 --> 00:13:35,314
"If you've been watching
longer than two hours,
252
00:13:35,397 --> 00:13:37,566
then display this."
253
00:13:37,650 --> 00:13:39,860
But for code
to impact most people's lives,
254
00:13:39,944 --> 00:13:42,696
most people had to be using computers,
255
00:13:42,780 --> 00:13:46,033
which meant computers
had to be easier, friendlier,
256
00:13:46,116 --> 00:13:50,621
and that required another big leap,
which started here,
257
00:13:50,704 --> 00:13:54,333
in a demo given by Doug Engelbart in 1968.
258
00:13:54,416 --> 00:13:56,752
[Doug] In a second,
we'll see the screen he's working
259
00:13:56,836 --> 00:13:58,337
and the way the tracking spot moves
260
00:13:58,420 --> 00:14:01,924
in conjunction with
movements of that mouse.
261
00:14:02,007 --> 00:14:04,176
People nowadays don't program
262
00:14:04,260 --> 00:14:07,680
by writing out statements
on a piece of paper
263
00:14:07,763 --> 00:14:11,433
and then handing them off to somebody
who types it in.
264
00:14:11,517 --> 00:14:15,229
You sit down at a screen.
You have a graphical user interface.
265
00:14:15,312 --> 00:14:17,898
Today, we call them GUIs.
266
00:14:17,982 --> 00:14:21,110
With GUIs, people can code
without typing at all.
267
00:14:22,528 --> 00:14:25,114
Or they can just use code more easily.
268
00:14:25,197 --> 00:14:30,160
You're typically operating in
a programming environment
269
00:14:30,244 --> 00:14:34,874
of the type that Alan and his companions
270
00:14:34,957 --> 00:14:36,375
created so beautifully
271
00:14:36,458 --> 00:14:40,588
at Xerox Palo Alto Research Center
in the early '70s.
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00:14:40,671 --> 00:14:42,756
Alan. This Alan.
273
00:14:42,840 --> 00:14:45,885
I think of him
as the father of personal computing
274
00:14:45,968 --> 00:14:50,556
because he was the first
to really articulate that vision.
275
00:14:50,639 --> 00:14:54,310
And I have to confess, at the time,
I thought it was science fiction.
276
00:14:54,393 --> 00:14:56,562
When big things really get done...
277
00:14:58,063 --> 00:14:59,690
there's usually a whole community.
278
00:14:59,773 --> 00:15:04,653
And, boy, Park was fantastic at it.
It was just like magic.
279
00:15:04,737 --> 00:15:08,449
The graphical user interface
allowed millions more people
280
00:15:08,532 --> 00:15:13,037
to use computers in a way
that is natural to them.
281
00:15:13,120 --> 00:15:17,082
When Xerox
first advertised GUIs in 1979,
282
00:15:17,166 --> 00:15:20,210
they showed how code
could change daily life.
283
00:15:20,294 --> 00:15:21,587
[man] You come into your office,
284
00:15:21,670 --> 00:15:24,965
and a Xerox machine
presents your morning mail on a screen.
285
00:15:25,049 --> 00:15:27,301
Soon, Xerox systems like this
286
00:15:27,384 --> 00:15:30,346
will help you manage
your most precious resource--
287
00:15:30,429 --> 00:15:31,722
information.
288
00:15:31,805 --> 00:15:33,390
There were people like me,
289
00:15:33,474 --> 00:15:36,477
and a lot of the people
in this research community
290
00:15:36,560 --> 00:15:38,062
wanted to make the world better.
291
00:15:38,145 --> 00:15:43,484
They had an idea that was deeply related
to human augmentation.
292
00:15:43,567 --> 00:15:46,570
Something that would interact with us,
293
00:15:46,654 --> 00:15:49,323
you know, the-the public,
the-the normal person,
294
00:15:49,406 --> 00:15:53,577
and make us capable of
doing more than we were before.
295
00:15:53,661 --> 00:15:56,205
It did make us capable of doing more.
296
00:15:56,288 --> 00:15:58,832
GUIs were a big jump up this spectrum.
297
00:15:59,458 --> 00:16:03,879
And then came
the next world-changing innovation.
298
00:16:03,963 --> 00:16:05,255
[dial-up drone]
299
00:16:05,339 --> 00:16:09,051
A new way to distribute everything
that we could make with code.
300
00:16:10,052 --> 00:16:11,720
On TV, people started predicting
301
00:16:11,804 --> 00:16:14,682
what sudden access to all this code
would mean.
302
00:16:14,765 --> 00:16:17,351
Imagine, if you will,
sitting down to your morning coffee,
303
00:16:17,434 --> 00:16:20,396
turning on your home computer
to read the day's newspaper.
304
00:16:20,479 --> 00:16:23,315
Imagine a world
where every word ever written,
305
00:16:23,399 --> 00:16:24,858
every picture ever painted,
306
00:16:24,942 --> 00:16:28,654
every film ever shot
could be viewed instantly in your home.
307
00:16:28,737 --> 00:16:33,617
I think we're actually on the cusp of
something exhilarating and terrifying.
308
00:16:33,701 --> 00:16:36,161
-It's just a tool, though, isn't it?
-No, it's not.
309
00:16:36,245 --> 00:16:40,624
The most impactful software products today
make use of all these innovations.
310
00:16:40,708 --> 00:16:45,129
One college student used
a high-level programming language, PHP,
311
00:16:45,212 --> 00:16:47,381
to make something
shared over the Internet,
312
00:16:47,464 --> 00:16:49,883
to be used on computers with GUIs.
313
00:16:49,967 --> 00:16:53,846
He described it
in his first ever TV interview in 2004.
314
00:16:53,929 --> 00:16:56,306
It's an online directory
that connects people
315
00:16:56,390 --> 00:16:59,435
through universities and colleges
through their social networks there.
316
00:16:59,518 --> 00:17:03,063
Now we're at a hundred thousand people,
so who knows where we're going next?
317
00:17:03,147 --> 00:17:06,734
Where we went
was more than 2,000,000,000 people
318
00:17:06,817 --> 00:17:08,610
on Facebook monthly.
319
00:17:08,694 --> 00:17:11,780
Today, coders shape
literally billions of people's lives.
320
00:17:11,864 --> 00:17:16,076
How they work, shop, eat, date, and chill.
321
00:17:16,160 --> 00:17:17,494
What are you doing right now?
322
00:17:17,578 --> 00:17:21,290
You're watching me
in a Netflix web browser.
323
00:17:23,292 --> 00:17:25,294
So Netflix itself is code,
324
00:17:25,377 --> 00:17:28,297
and it's being run in a web browser
that is code,
325
00:17:28,380 --> 00:17:33,927
which is being run on a computer
that was designed using code.
326
00:17:34,011 --> 00:17:36,388
It's-It's turtles all the way down, right?
327
00:17:37,639 --> 00:17:41,226
Great code is like being
the architect of a museum
328
00:17:41,310 --> 00:17:43,353
that millions of people think of
329
00:17:43,437 --> 00:17:46,106
and go and walk around
and use every day.
330
00:17:46,190 --> 00:17:49,526
I think there's nothing like writing code,
because it feels like pure creation.
331
00:17:49,610 --> 00:17:52,196
You have an idea
for how something should work,
332
00:17:52,279 --> 00:17:56,116
and then you try to sit down
in front of a computer
333
00:17:56,200 --> 00:17:58,035
and make that a reality.
334
00:17:58,118 --> 00:18:01,038
I think there's a lot of responsibility
for that role.
335
00:18:01,121 --> 00:18:04,041
You know, you have a speed limit.
336
00:18:04,124 --> 00:18:05,709
No more than 60 miles an hour.
337
00:18:06,627 --> 00:18:11,423
Fine. But what if you had a car,
and the computer said...
338
00:18:12,132 --> 00:18:15,719
"Well, this car is not gonna go faster
than 60 miles an hour"?
339
00:18:15,803 --> 00:18:17,930
That's a different way
of controlling your behavior.
340
00:18:18,013 --> 00:18:20,182
Often by controlling our choices...
341
00:18:20,849 --> 00:18:26,021
code in our live exerts
an almost more profound regulatory effect,
342
00:18:26,105 --> 00:18:28,398
uh, than the law can ever hope to.
343
00:18:28,482 --> 00:18:30,818
And that might be a great thing.
344
00:18:30,901 --> 00:18:35,239
There are around 6,000,000 car crashes
in the U.S. every year,
345
00:18:35,322 --> 00:18:39,660
and one analysis
found 94% are caused by the driver.
346
00:18:40,327 --> 00:18:43,163
Advancements in coding
could save millions of lives.
347
00:18:43,664 --> 00:18:47,334
But they can also put lives in danger
in new ways.
348
00:18:47,417 --> 00:18:51,004
I have something called
hypertrophic cardiomyopathy,
349
00:18:51,088 --> 00:18:56,343
um, which is the medical term
for the fact that I have a big heart.
350
00:18:56,426 --> 00:18:58,137
My heart is literally a big heart.
351
00:18:58,220 --> 00:19:00,889
It is about three times the size of
a normal person's heart.
352
00:19:00,973 --> 00:19:03,100
I found out when I was about 30,
353
00:19:03,183 --> 00:19:07,312
and so my risk of suddenly dying by 40
was just very large.
354
00:19:07,396 --> 00:19:09,982
And the electrophysiologist said,
"Well, this is no problem at all
355
00:19:10,065 --> 00:19:12,860
because you can get
a pacemaker defibrillator."
356
00:19:12,943 --> 00:19:14,987
This device runs on code.
357
00:19:15,654 --> 00:19:17,990
A couple years ago, when I was pregnant,
358
00:19:18,073 --> 00:19:20,117
my heart was palpitating.
359
00:19:20,200 --> 00:19:23,579
About a quarter of all women
have palpitations.
360
00:19:23,662 --> 00:19:25,038
It's perfectly normal.
361
00:19:25,122 --> 00:19:29,543
But my device thought that I was in
a dangerous rhythm, and it shocked me.
362
00:19:29,626 --> 00:19:34,047
Device manufacturers have no interest
in pregnant ladies getting shocked.
363
00:19:34,131 --> 00:19:36,508
It is literally the last thing they want.
364
00:19:36,592 --> 00:19:39,219
They just... haven't considered it.
365
00:19:39,303 --> 00:19:42,931
There is this huge set of decisions...
366
00:19:43,015 --> 00:19:47,436
and the people who do the programming
will be making them.
367
00:19:48,145 --> 00:19:53,650
And inevitably, there will be
some combination of circumstances
368
00:19:53,734 --> 00:19:56,111
that they will not have anticipated.
369
00:19:56,195 --> 00:20:02,117
So, what we try to teach
when we teach the craft of programming
370
00:20:02,201 --> 00:20:07,706
is how you think about
all these different conditions.
371
00:20:07,789 --> 00:20:13,212
How you try to be exhaustive
without becoming paralyzed
372
00:20:13,295 --> 00:20:16,048
by the number of things
that you might have to consider.
373
00:20:16,131 --> 00:20:18,425
And that will only become more true,
374
00:20:18,508 --> 00:20:21,678
because we've started coding
in a completely new way.
375
00:20:22,387 --> 00:20:25,933
In traditional coding,
you write instructions for a computer.
376
00:20:26,016 --> 00:20:30,270
But we're now able to give a computer
a bunch of inputs and a bunch of outputs
377
00:20:30,354 --> 00:20:33,815
and get it to write its own instructions.
378
00:20:33,899 --> 00:20:37,361
What you do is you give the computer...
379
00:20:38,320 --> 00:20:39,947
a lot of examples,
380
00:20:40,030 --> 00:20:43,742
and you say, "This is a party,
this is a party, this is a party." Right?
381
00:20:43,825 --> 00:20:47,204
And then you have other things.
A dentist's office--not a party.
382
00:20:47,287 --> 00:20:49,206
A classroom--not a party.
383
00:20:49,289 --> 00:20:51,541
So then the computer looks at these
384
00:20:51,625 --> 00:20:55,128
and tries to build
a classification system.
385
00:20:55,212 --> 00:20:57,130
This is machine learning.
386
00:20:57,214 --> 00:21:00,342
These days, if somebody says
artificial intelligence,
387
00:21:00,425 --> 00:21:01,510
this is what they mean.
388
00:21:01,593 --> 00:21:05,222
That's a whole different
kind of abstraction
389
00:21:05,305 --> 00:21:06,598
and way of doing things,
390
00:21:06,682 --> 00:21:11,520
because it doesn't really fit into the way
we stack these things up.
391
00:21:11,603 --> 00:21:13,689
We call them machine-learning algorithms
392
00:21:13,772 --> 00:21:18,026
because the computer is creating
its own set of directions to follow.
393
00:21:18,110 --> 00:21:19,736
But, of course, in the end,
394
00:21:19,820 --> 00:21:24,491
they too get translated into
tiny little instructions.
395
00:21:25,158 --> 00:21:28,412
Google Translate used to be
more than a million lines of code.
396
00:21:28,495 --> 00:21:32,749
That's people writing
million little instructions.
397
00:21:32,833 --> 00:21:38,338
Currently, Google Translate
is about 500 lines of code
398
00:21:38,422 --> 00:21:42,175
-that just calls in the machine learning.
-Suppose, because of an oversight,
399
00:21:42,259 --> 00:21:46,930
none of the photos of parties you put in
included any black or Hispanic people.
400
00:21:47,014 --> 00:21:49,308
The computer could decide
that a rule of parties
401
00:21:49,391 --> 00:21:52,728
is only white and Asian people
are invited.
402
00:21:52,811 --> 00:21:56,106
There's a lot of white
and Asian guys who program.
403
00:21:56,189 --> 00:22:01,194
We should absolutely expand
who gets to be in that design room
404
00:22:01,278 --> 00:22:02,404
for a million reasons.
405
00:22:02,487 --> 00:22:05,282
They will ask better questions
if there is more life experience.
406
00:22:05,365 --> 00:22:08,952
But, in the end, if you're feeding
your machine-learning system data,
407
00:22:09,036 --> 00:22:13,165
say, criminal-justice system that has
structural racism built into that data,
408
00:22:13,248 --> 00:22:15,459
and let's say
your machine-learning programmers
409
00:22:15,542 --> 00:22:20,380
look like a Benetton ad,
different races, different sort of faces,
410
00:22:20,464 --> 00:22:22,549
different social backgrounds,
411
00:22:22,632 --> 00:22:25,260
that machine-learning system
is still gonna learn from the data.
412
00:22:25,344 --> 00:22:28,013
Without people
actively correcting for that,
413
00:22:28,096 --> 00:22:31,725
historical data will lead us
to repeat the mistakes of the past.
414
00:22:33,769 --> 00:22:38,440
The story of coding
is one of human ambition and creativity.
415
00:22:38,523 --> 00:22:41,485
[man] Liftoff of the Falcon 9 rocket.
416
00:22:41,568 --> 00:22:43,987
We have seen
what we thought was unseeable.
417
00:22:44,863 --> 00:22:46,239
A black hole.
418
00:22:46,323 --> 00:22:50,160
We're building a new world
with more and more intuitive tools
419
00:22:50,243 --> 00:22:55,999
that a greater number of people can use
to help make sure that world is better.
420
00:22:56,083 --> 00:22:57,501
We have been on a journey
421
00:22:57,584 --> 00:23:00,379
to make computers more accessible
to human beings
422
00:23:00,462 --> 00:23:02,381
and to a greater set of human beings.
423
00:23:02,464 --> 00:23:07,135
We're seeing this revolution play out
before our eyes in the past 50 years,
424
00:23:07,219 --> 00:23:09,763
and that's why it's so exciting
to be alive today.
425
00:23:09,846 --> 00:23:11,973
It's very important to really remember
426
00:23:12,099 --> 00:23:16,895
everything you use on your computer
was created by some human being.
427
00:23:16,978 --> 00:23:18,730
You can be one of those people, actually,
428
00:23:18,814 --> 00:23:21,191
and it's really important
you become one of those people.
429
00:23:21,274 --> 00:23:24,111
You can actually change the world
in a really fundamental way.
430
00:23:24,194 --> 00:23:26,571
There's a world that's gonna be run
431
00:23:26,655 --> 00:23:30,784
using machine learning
and data and traditional coding
432
00:23:30,867 --> 00:23:32,244
in more and more ways.
433
00:23:32,327 --> 00:23:35,080
And what we have to do
as a society is say,
434
00:23:35,163 --> 00:23:38,166
"Okay. We've got this
potent new technology,
435
00:23:38,250 --> 00:23:43,046
and in some ways, it could be great,
but it's not gonna be great by itself."
436
00:23:44,756 --> 00:23:46,758
[closing music playing]