Insightful human portraits made from data | R. Luke DuBois

116,328 views ใƒป 2016-05-19

TED


ืื ื ืœื—ืฅ ืคืขืžื™ื™ื ืขืœ ื”ื›ืชื•ื‘ื™ื•ืช ื‘ืื ื’ืœื™ืช ืœืžื˜ื” ื›ื“ื™ ืœื”ืคืขื™ืœ ืืช ื”ืกืจื˜ื•ืŸ.

ืžืชืจื’ื: Shlomo Adam ืžื‘ืงืจ: Sigal Tifferet
00:12
So I'm an artist,
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ืื ื™ ืืžืŸ,
00:14
but a little bit of a peculiar one.
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ืื‘ืœ ืืžืŸ ืงืฆืช ืฉื•ื ื”.
00:16
I don't paint.
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ืื ื™ ืœื ืžืฆื™ื™ืจ.
00:18
I can't draw.
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ืื ื™ ืœื ื™ื•ื“ืข ืœืฆื™ื™ืจ.
00:20
My shop teacher in high school wrote that I was a menace
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ื”ืžื•ืจื” ืฉืœื™ ืœืžืœืื›ื” ื›ืชื‘ ื‘ืชืขื•ื“ื” ืฉืœื™ ืฉืื ื™ ืžืกื•ื›ืŸ.
00:24
on my report card.
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00:25
You probably don't really want to see my photographs.
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ืื ื™ ื‘ื˜ื•ื— ืฉืœื ืชืจืฆื• ืœืจืื•ืช ืชืžื•ื ื•ืช ืฉืฆื™ืœืžืชื™.
00:29
But there is one thing I know how to do:
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ืื‘ืœ ื™ืฉ ืžืฉื”ื• ืฉืื ื™ ื›ืŸ ื™ื•ื“ืข ืœืขืฉื•ืช:
00:31
I know how to program a computer.
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ืื ื™ ื™ื•ื“ืข ืœืชื›ื ืช ืžื—ืฉื‘ื™ื. ืื ื™ ื™ื•ื“ืข ืชื™ื›ื ื•ืช.
00:33
I can code.
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00:34
And people will tell me that 100 years ago,
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ืื•ืžืจื™ื ืœื™ ืฉืœืคื ื™ 100 ืฉื ื™ื
00:38
folks like me didn't exist,
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ืื ืฉื™ื ื›ืžื•ื ื™ ืœื ื”ื™ื• ืงื™ื™ืžื™ื,
00:39
that it was impossible,
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ืฉื–ื” ืœื ื”ื™ื” ืืคืฉืจื™,
00:41
that art made with data is a new thing,
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ืฉืืžื ื•ืช ืฉื ื•ืฆืจืช ื‘ืขื–ืจืช ื ืชื•ื ื™ื ื”ื™ื ื“ื‘ืจ ื—ื“ืฉ,
00:44
it's a product of our age,
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ืชื•ืฆืจ ืฉืœ ื”ืขื™ื“ืŸ ืฉืœื ื•,
00:46
it's something that's really important
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ืžืฉื”ื• ืฉื—ืฉื•ื‘ ืœืจืื•ืชื• ื›"ืขื›ืฉื•ื•ื™" ืžืื“,
00:48
to think of as something that's very "now."
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00:50
And that's true.
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ื•ื–ื” ื ื›ื•ืŸ.
00:52
But there is an art form that's been around for a very long time
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ืื‘ืœ ื™ืฉ ืฆื•ืจืช ืืžื ื•ืช ืฉืงื™ื™ืžืช ื›ื‘ืจ ื–ืžืŸ ืจื‘ ืžืื“
00:56
that's really about using information,
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ื•ื”ื™ื ืงืฉื•ืจื” ื‘ืฉื™ืžื•ืฉ ื‘ืžื™ื“ืข, ืžื™ื“ืข ืžื•ืคืฉื˜,
00:58
abstract information,
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01:00
to make emotionally resonant pieces.
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ื›ื“ื™ ืœื™ืฆื•ืจ ื™ืฆื™ืจื•ืช ื‘ืขืœื•ืช ืชื”ื•ื“ื” ืจื’ืฉื™ืช:
ืžื•ืกื™ืงื”.
01:03
And it's called music.
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[ื ืชื•ื ื™ื ืžื•ืฆืงื™ื 4, 2009]
01:05
We've been making music for tens of thousands of years, right?
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ืื ื• ื™ื•ืฆืจื™ื ืžื•ืกื™ืงื” ื›ื‘ืจ ืขืฉืจื•ืช ืืœืคื™ ืฉื ื™ื, ื ื›ื•ืŸ?
01:09
And if you think about what music is --
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ื•ืื ื—ื•ืฉื‘ื™ื ืžื”ื™ ืžื•ืกื™ืงื” --
01:11
notes and chords and keys and harmonies and melodies --
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ืชื•ื•ื™ื, ืืงื•ืจื“ื™ื, ืžืคืชื—ื•ืช, ื”ืจืžื•ื ื™ื•ืช ื•ืžืœื•ื“ื™ื•ืช --
01:14
these things are algorithms.
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ื”ื“ื‘ืจื™ื ื”ืืœื” ื”ื ืืœื’ื•ืจื™ืชืžื™ื, ืžืขืจื›ื•ืช
01:15
These things are systems
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01:17
that are designed to unfold over time,
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ืฉื ื•ืขื“ื• ืœื”ืชืคืชื— ืขืœ ืฆื™ืจ ื–ืžืŸ ื•ืœืขื•ืจืจ ื‘ื ื• ืจื’ืฉ.
01:20
to make us feel.
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(ืžื•ืกื™ืงื”)
01:22
I came to the arts through music.
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ื”ื’ืขืชื™ ืœืืžื ื•ืช ื“ืจืš ื”ืžื•ืกื™ืงื”. ืœืžื“ืชื™ ื”ืœื—ื ื”,
01:23
I was trained as a composer,
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01:25
and about 15 years ago, I started making pieces
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ื•ืœืคื ื™ ื›-15 ืฉื ื” ื”ืชื—ืœืชื™ ืœื›ืชื•ื‘ ื™ืฆื™ืจื•ืช
01:28
that were designed to look at the intersection
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ืฉื‘ื—ื ื• ืืช ื”ืžืคื’ืฉ ืฉื‘ื™ืŸ ืฆืœื™ืœ ื•ืชืžื•ื ื”,
01:31
between sound and image,
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01:33
to use an image to unveil a musical structure
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ืœื”ืฉืชืžืฉ ื‘ื“ื™ืžื•ื™ ื—ื–ื•ืชื™ ื›ื“ื™ ืœื”ืฆื™ื’ ืžื‘ื ื” ืžื•ืกื™ืงืœื™
01:35
or to use a sound to show you something interesting
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ืื• ืœื”ืฉืชืžืฉ ื‘ืฆืœื™ืœ ื›ื“ื™ ืœื”ืจืื•ืช ืžืฉื”ื• ืžืขื ื™ื™ืŸ
01:38
about something that's usually pictorial.
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ืฉื ื•ื’ืข ืœืžืฉื”ื• ืฉื”ื•ื ื‘ื“"ื› ืฆื™ื•ืจื™.
01:40
So what you're seeing on the screen is literally being drawn
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ืžื” ืฉืืชื ืจื•ืื™ื ืขืœ ื”ืžืกืš ืžืฆื˜ื™ื™ืจ ื‘ื–ืžืŸ ืืžื™ืชื™
01:44
by the musical structure of the musicians onstage,
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ืข"ื™ ื”ืžื‘ื ื” ื”ืžื•ืกื™ืงืœื™ ืฉื™ื•ืฆืจื™ื ื”ืžื•ืกื™ืงืื™ื ื”ืžื‘ืฆืขื™ื,
01:47
and there's no accident that it looks like a plant,
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ื•ื–ื” ืœื ื‘ืžืงืจื” ื ืจืื” ื›ืžื• ืฆืžื—,
01:49
because the underlying algorithmic biology of the plant
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ื›ื™ ืืœื’ื•ืจื™ืชื-ื”ื™ืกื•ื“ ื”ื‘ื™ื•ืœื•ื’ื™ ืฉืœ ื”ืฆืžื—
01:53
is what informed the musical structure in the first place.
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ื”ื•ื ืžืงื•ืจ ื”ืžื™ื“ืข ืฉืœ ื”ืžื‘ื ื” ื”ืžื•ืกื™ืงืœื™.
01:56
So once you know how to do this, once you know how to code with media,
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ืื– ื›ืฉื™ื•ื“ืขื™ื ืœืขืฉื•ืช ื–ืืช, ื›ืฉื™ื•ื“ืขื™ื ืœืชื›ื ืช ื‘ืžื“ื™ื”,
01:59
you can do some pretty cool stuff.
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ืืคืฉืจ ืœื™ืฆื•ืจ ื“ื‘ืจื™ื ืžืžืฉ ืžื’ื ื™ื‘ื™ื.
02:02
This is a project I did for the Sundance Film Festival.
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ื–ื”ื• ืžื™ื–ื ืฉื™ืฆืจืชื™ ืขื‘ื•ืจ ืคืกื˜ื™ื‘ืœ ื”ืกืจื˜ื™ื "ืกื ื“ืื ืก".
02:05
Really simple idea: you take every Academy Award Best Picture,
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ื”ืจืขื™ื•ืŸ ืžืžืฉ ืคืฉื•ื˜: ืœื•ืงื—ื™ื ื›ืœ ืกืจื˜ ื–ื•ื›ื” ืื•ืกืงืจ,
02:11
you speed it up to one minute each
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ืžืื™ืฆื™ื ืื•ืชื• ืœื”ืงืจื ื” ื‘ืช ื“ืงื” ืื—ืช
02:13
and string them all together.
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ื•ืฉื•ื–ืจื™ื ืืช ื›ื•ืœื ื™ื—ื“.
02:15
And so in 75 minutes, I can show you the history of Hollywood cinema.
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ืื– ื‘ืžืฉืš 75 ื“ืงื•ืช ืื ื™ ื™ื›ื•ืœ ืœื”ืจืื•ืช ืœื›ื
ืืช ื”ื”ื™ืกื˜ื•ืจื™ื” ืฉืœ ื”ืงื•ืœื ื•ืข ื”ื”ื•ืœื™ื•ื•ื“ื™.
02:19
And what it really shows you is the history of editing
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ื•ืœืžืขืฉื” ื–ื” ืžืฆื™ื’ ืืช ื”ื”ื™ืกื˜ื•ืจื™ื” ืฉืœ ื”ืขืจื™ื›ื” ื‘ืงื•ืœื ื•ืข ื”ื”ื•ืœื™ื•ื•ื“ื™.
02:22
in Hollywood cinema.
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02:23
So on the left, we've got Casablanca; on the right, we've got Chicago.
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ืžืฉืžืืœ ืจื•ืื™ื ืืช "ืงื–ื‘ืœื ืงื”", ืžื™ืžื™ืŸ, ืืช "ืฉื™ืงื’ื•".
02:27
And you can see that Casablanca is a little easier to read.
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ื•ืืชื ืจื•ืื™ื ืฉืืช "ืงื–ื‘ืœื ืงื”" ืงืฆืช ืงืœ ื™ื•ืชืจ ืœืจืื•ืช
02:30
That's because the average length of a cinematic shot in the 1940s
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ื›ื™ ื”ืื•ืจืš ื”ืžืžื•ืฆืข ืฉืœ "ืฉื•ื˜" ืงื•ืœื ื•ืขื™ ื‘ืฉื ื•ืช ื”-40 ืฉืœ ื”ืžืื” ื”-20
02:34
was 26 seconds,
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ื”ื™ื” 26 ืฉื ื™ื•ืช,
02:35
and now it's around six seconds.
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ื•ื›ื™ื•ื ืื•ืจื›ื• ื›-6 ืฉื ื™ื•ืช.
02:38
This is a project that was inspired
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ื–ื”ื• ืžื™ื–ื ืฉื”ื•ืฉืคืข
02:40
by some work that was funded by the US Federal Government
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ืžืžื™ื–ื ืฉืžื™ืžืŸ ื”ืžืžืฉืœ ื”ืคื“ืจืœื™ ื‘ืชื—ื™ืœืช ื”ืžืื” ื”-21,
02:43
in the early 2000s,
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02:44
to look at video footage and find a specific actor in any video.
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ื‘ืžื˜ืจื” ืœื‘ื—ื•ืŸ ืกืจื˜ื•ื ื™ื ื•ืœืืชืจ ืžื™ ืžืฉื—ืง ื‘ื›ืœ ืกืจื˜ื•ืŸ.
02:51
And so I repurposed this code to train a system on one person
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ืื– ื”ืกื‘ืชื™ ืืช ื”ืชื•ื›ื ื” ื”ื–ืืช
ืœืžืขืจื›ืช ืžืขืงื‘ ืื—ืจื™ ืื“ื ืื—ื“ ื‘ืชืจื‘ื•ืช ืฉืœื ื•
02:56
in our culture who would never need to be surveilled in that manner,
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ืฉืœื ื™ื”ื™ื” ืฉื•ื ืฆื•ืจืš ืœืขืงื•ื‘ ืื—ืจื™ื• ื›ืš:
03:00
which is Britney Spears.
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ื‘ืจื™ื˜ื ื™ ืกืคื™ืจืก.
03:01
I downloaded 2,000 paparazzi photos of Britney Spears
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ื”ื•ืจื“ืชื™ 2,000 ืฆื™ืœื•ืžื™ ืคืคืจืืฆื™ ืฉืœ ื‘ืจื™ื˜ื ื™ ืกืคื™ืจืก
03:05
and trained my computer to find her face
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ื•ืœื™ืžื“ืชื™ ืืช ื”ืžื—ืฉื‘ ืฉืœื™ ืœืืชืจ ืืช ืคื ื™ื”,
03:07
and her face alone.
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ื•ืืช ืคื ื™ื” ื‘ืœื‘ื“.
03:09
I can run any footage of her through it and will center her eyes in the frame,
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ืื ื™ ื™ื›ื•ืœ ืœื”ืจื™ืฅ ื›ืœ ืกืจื˜ื•ืŸ ืฉืœื” ื•ื”ืชื•ื›ื ื” ืชืžืจื›ื– ืืช ืขื™ื ื™ื”,
03:13
and this sort of is a little double commentary
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ื•ื–ื• ืžืขื™ืŸ ืคืจืฉื ื•ืช ื›ืคื•ืœื” ืขืœ ื”ืžืขืงื‘ื™ื ื‘ื—ื‘ืจื” ืฉืœื ื•.
03:15
about surveillance in our society.
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03:17
We are very fraught with anxiety about being watched,
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ืื ื• ืžืœืื™ ืคื—ื“ื™ื ื‘ื ื•ืฉื ื”ืžืขืงื‘ ืื—ืจื™ื ื•,
03:20
but then we obsess over celebrity.
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ืื‘ืœ ื›ืคื™ื™ืชื™ื™ื ื‘ืงืฉืจ ืœื—ื™ื™ื”ื ืฉืœ ื™ื“ื•ืขื ื™ื.
03:24
What you're seeing on the screen here is a collaboration I did
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ืžื” ืฉืืชื ืจื•ืื™ื ืขืœ ื”ืžืกืš ื”ื•ื ืคืจื™ ืฉื™ืชื•ืฃ-ืคืขื•ืœื” ืฉืœื™
03:27
with an artist named Liรกn Amaris.
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ืขื ืืžื ื™ืช ื‘ืฉื ืœื™ืืŸ ืืžืืจื™ืก.
03:30
What she did is very simple to explain and describe,
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ืืช ืžื” ืฉื”ื™ื ืขืฉืชื” ืงืœ ืžืื“ ืœื”ืกื‘ื™ืจ ื•ืœืชืืจ,
03:34
but very hard to do.
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ืื‘ืœ ืงืฉื” ืžืื“ ืœืขืฉื•ืช.
03:35
She took 72 minutes of activity,
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ื”ื™ื ืœืงื—ื” 72 ื“ืงื•ืช ืฉืœ ืคืขื™ืœื•ืช
03:39
getting ready for a night out on the town,
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ืฉืœ ื”ื›ื ื•ืช ืœื‘ื™ืœื•ื™ ืœื™ืœื™ ื‘ืขื™ืจ,
03:41
and stretched it over three days
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ืžืชื—ื” ืื•ืชืŸ ืขืœ ืคื ื™ 3 ื™ืžื™ื
03:43
and performed it on a traffic island in slow motion in New York City.
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ื•ื‘ื™ืฆืขื” ื–ืืช ื‘ื”ื™ืœื•ืš ืื™ื˜ื™ ืขืœ ืื™-ืชื ื•ืขื” ื‘ืขื™ืจ ื ื™ื•-ื™ื•ืจืง.
03:47
I was there, too, with a film crew.
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ื’ื ืื ื™ ื”ื™ื™ืชื™ ืฉื, ืขื ืฆื•ื•ืช ืฆื™ืœื•ื.
ื”ืกืจื˜ื ื• ืืช ื”ื›ืœ.
03:50
We filmed the whole thing,
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ื•ืื– ื”ืคื›ื ื• ืืช ื”ืชื”ืœื™ืš, ื”ืืฆื ื• ืืช ื–ื” ืฉื•ื‘ ืœ-72 ื“ืงื•ืช,
03:51
and then we reversed the process, speeding it up to 72 minutes again,
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03:54
so it looks like she's moving normally
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ื›ื“ื™ ืฉื™ื™ืจืื” ื›ืื™ืœื• ืฉื”ื™ื ืžืชื ื•ืขืขืช ื›ืจื’ื™ืœ
03:56
and the whole world is flying by.
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ื›ืฉื›ืœ ื”ืขื•ืœื ืžืกืชื—ืจืจ ืกื‘ื™ื‘ื”.
03:59
At a certain point, I figured out
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ื‘ืฉืœื‘ ืžืกื•ื™ื ื”ื‘ื ืชื™ ืฉื‘ืขืฆื ืื ื™ ื™ื•ืฆืจ ื“ื™ื•ืงื ืื•ืช.
04:01
that what I was doing was making portraits.
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04:05
When you think about portraiture, you tend to think about stuff like this.
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ื›ืฉื—ื•ืฉื‘ื™ื ืขืœ ื™ืฆื™ืจืช ื“ื™ื•ืงื ืื•ืช, ื‘ื“"ื› ื—ื•ืฉื‘ื™ื ืขืœ ื“ื‘ืจื™ื ื›ืืœื”:
ืžืฉืžืืœ, ื–ื”ื• ื’ื™ืœื‘ืจื˜ ืกื˜ื™ื•ืืจื˜.
04:09
The guy on the left is named Gilbert Stuart.
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ื”ื•ื ื‘ืžื™ื“ื” ืจื‘ื” ื”ื“ื™ื•ืงื ืื™ ื”ืืžื™ืชื™ ื”ืืžืจื™ืงื ื™ ื”ืจืืฉื•ืŸ.
04:11
He's sort of the first real portraitist of the United States.
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04:14
And on the right is his portrait of George Washington from 1796.
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ื•ืžื™ืžื™ืŸ ื–ื”ื• ื”ื“ื™ื•ืงืŸ ืฉื™ืฆืจ ืฉืœ ื’'ื•ืจื’' ื•ื•ืฉื™ื ื’ื˜ื•ืŸ, ืž-1796,
04:17
This is the so-called Lansdowne portrait.
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ื”ืžื›ื•ื ื” "ื“ื™ื•ืงืŸ ืœื ืกื“ืื•ืŸ".
04:19
And if you look at this painting, there's a lot of symbolism, right?
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ื›ืฉืžื‘ื™ื˜ื™ื ื‘ืฆื™ื•ืจ ื”ื–ื” ืจื•ืื™ื ืกืžืœื™ื•ืช ืจื‘ื”, ื ื›ื•ืŸ?
04:22
We've got a rainbow out the window. We've got a sword.
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ืจื•ืื™ื ืงืฉืช ื‘ื—ืœื•ืŸ, ื™ืฉ ืฉื ื—ืจื‘.
04:25
We've got a quill on the desk.
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ืขืœ ื”ืฉื•ืœื—ืŸ ื™ืฉ ืœื ื• ืขื˜ ื ื•ืฆื”.
04:27
All of these things are meant to evoke
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ื”ื›ืœ ื ื•ืขื“ ืœื”ืฆื™ื’ ืืช ื’'ื•ืจื’' ื•ื•ืฉื™ื ื’ื˜ื•ืŸ ื›ืื‘ื™ ื”ืื•ืžื”.
04:29
George Washington as the father of the nation.
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04:31
This is my portrait of George Washington.
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ื”ื ื” ื”ื“ื™ื•ืงืŸ ืฉืœื™, ืฉืœ ื’'ื•ืจื’' ื•ื•ืฉื™ื ื’ื˜ื•ืŸ.
04:35
And this is an eye chart,
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ื–ืืช ื›ืจื–ื” ืฉืœ ื‘ื“ื™ืงืช ืจืื™ื”,
04:38
only instead of letters, they're words.
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ืื‘ืœ ื‘ืžืงื•ื ืื•ืชื™ื•ืช, ื™ืฉ ื‘ื” ืžืœื™ื.
04:41
And what the words are is the 66 words
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ืืœื• ื”ืŸ 66 ื”ืžืœื™ื ื‘ื ืื•ืžื™ื ืœืื•ืžื” ืฉืœ ื’'ื•ืจื’' ื•ื•ืฉื™ื ื’ื˜ื•ืŸ,
04:44
in George Washington's State of the Union addresses
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04:46
that he uses more than any other president.
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ืฉื‘ื”ืŸ ื”ื•ื ื”ืฉืชืžืฉ ื™ื•ืชืจ ืžื›ืœ ื ืฉื™ื ืื—ืจ.
04:50
So "gentlemen" has its own symbolism and its own rhetoric.
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ืœืžื™ืœื” "ื’'ื ื˜ืœืžื ื™ื" ื™ืฉ ืกืžืœื™ื•ืช ื•ืฉื™ืžื•ืฉ ืจื˜ื•ืจื™ ืžืฉืœื”,
04:54
And it's really kind of significant that that's the word he used the most.
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ื•ื™ืฉ ื—ืฉื™ื‘ื•ืช ืœื›ืš ืฉื‘ื” ื”ื•ื ื”ืฉืชืžืฉ ื™ื•ืชืจ ืžื›ืœ.
04:58
This is the eye chart for George W. Bush,
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ื–ืืช ื‘ื“ื™ืงืช ื”ืจืื™ื™ื” ืฉืœ ื’'ื•ืจื’' ื•ื•' ื‘ื•ืฉ,
ืฉื›ื™ื”ืŸ ื›ื ืฉื™ื ื›ืฉื™ืฆืจืชื™ ืืช ื–ื”.
05:01
who was president when I made this piece.
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ื•ื”ืื•ืคืŸ ื‘ื• ื”ื’ืขื ื• ืœื›ืืŸ,
05:04
And how you get there,
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05:05
from "gentlemen" to "terror" in 43 easy steps,
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ืž"ื’'ื ื˜ืœืžื ื™ื" ืœ"ื˜ืจื•ืจ" ื‘-43 ืฉืœื‘ื™ื ืงืœื™ื,
05:08
tells us a lot about American history,
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ืื•ืžืจ ื”ืจื‘ื” ืขืœ ื”ื”ื™ืกื˜ื•ืจื™ื” ื”ืืžืจื™ืงื ื™ืช,
05:10
and gives you a different insight
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ื•ื ื•ืชืŸ ืœื›ื ืชื•ื‘ื ื” ืฉื•ื ื” ืžืืฉืจ ืื™ืœื• ื”ื‘ื˜ืชื ื‘ืกื“ืจืช ืฆื™ื•ืจื™ื.
05:12
than you would have looking at a series of paintings.
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05:15
These pieces provide a history lesson of the United States
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ื”ื™ืฆื™ืจื•ืช ื”ืืœื” ืžืกืคืงื•ืช ืฉื™ืขื•ืจ ื‘ื“ื‘ืจื™ ื™ืžื™ื” ืฉืœ ืืžืจื™ืงื”
05:19
through the political rhetoric of its leaders.
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ื“ืจืš ื”ืจื˜ื•ืจื™ืงื” ื”ืคื•ืœื™ื˜ื™ืช ืฉืœ ืžื ื”ื™ื’ื™ื”.
05:21
Ronald Reagan spent a lot of time talking about deficits.
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ืจื•ื ืœื“ ืจื™ื™ื’ืŸ ื“ื™ื‘ืจ ื”ืžื•ืŸ ืขืœ ื’ืจืขื•ื ื•ืช.
05:25
Bill Clinton spent a lot of time
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ื‘ื™ืœ ืงืœื™ื ื˜ื•ืŸ ื“ื™ื‘ืจ ื”ืžื•ืŸ
05:26
talking about the century in which he would no longer be president,
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ืขืœ ื”ืžืื” ื‘ื” ื›ื‘ืจ ืœื ื™ื›ื”ืŸ ื›ื ืฉื™ื,
ืื‘ืœ ืื•ืœื™ ืืฉืชื• ื›ืŸ.
05:30
but maybe his wife would be.
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05:33
Lyndon Johnson was the first President
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ืœื™ื ื“ื•ืŸ ื’'ื•ื ืกื•ืŸ ื”ื™ื” ื”ื ืฉื™ื ื”ืจืืฉื•ืŸ
05:35
to give his State of the Union addresses on prime-time television;
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ืฉื ืฉื ืืช ื ืื•ืžื™ื• ืœืื•ืžื” ื‘ืฉืขื•ืช ืฆืคื™ื™ืช-ืฉื™ื ื‘ื˜ืœื•ื•ื™ื–ื™ื”;
ื”ื•ื ืคืชื— ื›ืœ ืคื™ืกืงื” ื‘ืžื™ืœื” "ื”ืขืจื‘".
05:39
he began every paragraph with the word "tonight."
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ื•ืจื™ืฆ'ืจื“ ื ื™ืงืกื•ืŸ, ืื• ื ื›ื•ืŸ ื™ื•ืชืจ, ื›ื•ืชื‘ ื”ื ืื•ืžื™ื ืฉืœื•, ื•ื•ื™ืœื™ืื ืกืืคื™ื™ืจ,
05:41
And Richard Nixon, or more accurately, his speechwriter,
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05:44
a guy named William Safire,
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05:45
spent a lot of time thinking about language
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ื—ืฉื‘ ื”ืžื•ืŸ ืขืœ ื”ืฉื™ืžื•ืฉ ื‘ืฉืคื”,
05:47
and making sure that his boss portrayed a rhetoric of honesty.
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ื•ื”ืฉืชื“ืœ ืžืื“ ืฉื”ื‘ื•ืก ืฉืœื• ื™ืฉื“ืจ ื‘ื“ื‘ืจื™ื• ื›ื ื•ืช.
05:51
This project is shown as a series of monolithic sculptures.
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ื”ืžื™ื–ื ื”ื–ื” ืžื•ืฆื’ ื›ืกื“ืจืช ืคืกืœื™ ืขื ืง.
05:54
It's an outdoor series of light boxes.
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ื–ืืช ืชืฆื•ื’ืช-ื—ื•ืฅ ืฉืœ ืชื™ื‘ื•ืช ืชืื•ืจื”.
05:56
And it's important to note that they're to scale,
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ื•ื—ืฉื•ื‘ ืœืฆื™ื™ืŸ ืฉื”ืŸ ื‘ืงื ื” ืžื™ื“ื” ื ื›ื•ืŸ,
05:59
so if you stand 20 feet back and you can read between those two black lines,
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ื›ืš ืฉืื ืชืขืžื“ื• ื‘ืžืจื—ืง 6 ืžื˜ืจื™ื ื•ืชื•ื›ืœื• ืœืงืจื•ื ื‘ื™ืŸ ืฉื ื™ ื”ืงื•ื•ื™ื ื”ืฉื—ื•ืจื™ื,
06:02
you have 20/20 vision.
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ื”ืจื™ ืฉื”ืจืื™ื™ื” ืฉืœื›ื ืžืฆื•ื™ื ืช.
(ืฆื—ื•ืง)
06:04
(Laughter)
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ื–ื”ื• ื“ื™ื•ืงืŸ, ื•ื™ืฉ ื”ืžื•ืŸ ื›ืืœื”.
06:05
This is a portrait. And there's a lot of these.
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06:07
There's a lot of ways to do this with data.
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ื™ืฉ ื”ืžื•ืŸ ื“ืจื›ื™ื ืœืขืฉื•ืช ื–ืืช ื‘ืขื–ืจืช ื ืชื•ื ื™ื.
06:10
I started looking for a way
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ื‘ื”ืชื—ืœื” ื—ื™ืคืฉืชื™ ื“ืจืš ืœื™ืฆื•ืจ ื“ื™ื•ืงื ืื•ืช ื‘ืื•ืคืŸ ื“ืžื•ืงืจื˜ื™ ื™ื•ืชืจ,
06:12
to think about how I can do a more democratic form of portraiture,
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06:17
something that's more about my country and how it works.
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ืžืฉื”ื• ืฉื ื•ื’ืข ื™ื•ืชืจ ืœืืจืฅ ืฉืœื™ ื•ืื™ืš ื”ื™ื ืžืชืคืงื“ืช.
06:21
Every 10 years, we make a census in the United States.
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ืžื™ื“ื™ 10 ืฉื ื™ื ืื ื• ืขื•ืจื›ื™ื ื‘ืืจื”"ื‘ ืžื™ืคืงื“.
06:25
We literally count people,
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ืื ื• ืžืžืฉ ืกื•ืคืจื™ื ื‘ื ื™-ืื“ื,
06:27
find out who lives where, what kind of jobs we've got,
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ืžื’ืœื™ื ืžื™ ื—ื™ ืื™ืคื”, ื‘ืžื” ืื ืฉื™ื ืขื•ื‘ื“ื™ื,
06:30
the language we speak at home.
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ื‘ืื™ื–ื• ืฉืคื” ืžื“ื‘ืจื™ื ื‘ื‘ื™ืช,
06:31
And this is important stuff -- really important stuff.
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ื•ื–ื” ื—ืฉื•ื‘, ื—ืฉื•ื‘ ืžืื“.
06:34
But it doesn't really tell us who we are.
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ืื‘ืœ ื–ื” ืœื ื‘ืืžืช ืื•ืžืจ ืœื ื• ืžื™ ืื ื—ื ื•.
06:36
It doesn't tell us about our dreams and our aspirations.
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ื–ื” ืœื ื‘ืืžืช ืžืกืคืจ ืขืœ ื—ืœื•ืžื•ืชื™ื ื• ื•ืฉืื™ืคื•ืชื™ื ื•.
06:39
And so in 2010, I decided to make my own census.
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ืื– ื‘-2010 ื”ื—ืœื˜ืชื™ ืœืขืจื•ืš ืžื™ืคืงื“ ืžืฉืœื™.
06:42
And I started looking for a corpus of data
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ื”ืชื—ืœืชื™ ืœื—ืคืฉ ื’ื•ืฃ ื ืชื•ื ื™ื
06:46
that had a lot of descriptions written by ordinary Americans.
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ืฉืžื›ื™ืœ ื”ืจื‘ื” ืชื™ืื•ืจื™ื ืฉื ื›ืชื‘ื• ื‘ื™ื“ื™ ืืžืจื™ืงื ื™ื ืจื’ื™ืœื™ื.
06:49
And it turns out
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ื•ืžืกืชื‘ืจ ืฉืงื™ื™ื ื’ื•ืฃ ื ืชื•ื ื™ื ื›ื–ื”
06:50
that there is such a corpus of data
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ืฉืจืง ืžื—ื›ื” ืฉื™ืฉืชืžืฉื• ื‘ื•.
06:52
that's just sitting there for the taking.
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06:54
It's called online dating.
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ื”ื•ื ืงืจื•ื™ "ื”ื™ื›ืจื•ื™ื•ืช ืžืงื•ื•ื ื•ืช".
06:56
So in 2010, I joined 21 different online dating services,
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ืื– ื‘-2010 ื ืจืฉืžืชื™ ืœ-21 ืฉื™ืจื•ืชื™ ื”ื™ื›ืจื•ื™ื•ืช ืžืงื•ื•ื ื™ื,
07:01
as a gay man, a straight man, a gay woman and a straight woman,
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ื›ื’ื‘ืจ ื”ื•ืžื•, ื›ื’ื‘ืจ ื”ื˜ืจื•ืกืงืกื•ืืœื™, ื›ืื™ืฉื” ืœืกื‘ื™ืช ื•ื›ืื™ืฉื” ื”ื˜ืจื•ืกืงืกื•ืืœื™ืช,,
07:04
in every zip code in America
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ื‘ื›ืœ ืื–ื•ืจ ืžื™ืงื•ื“ ื‘ืืžืจื™ืงื”
07:06
and downloaded about 19 million people's dating profiles --
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ื•ื”ื•ืจื“ืชื™ ื›-19 ืžื™ืœื™ื•ืŸ ืคืจื•ืคื™ืœื™ ื”ื›ืจื•ื™ื•ืช --
07:09
about 20 percent of the adult population of the United States.
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ื›-20% ืžื›ืœ ื”ืื•ื›ืœื•ืกื™ื” ื”ื‘ื•ื’ืจืช ื‘ืืจื”"ื‘.
07:13
I have obsessive-compulsive disorder.
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ื™ืฉ ืœื™ ื”ืคืจืขื” ื˜ื•ืจื“ื ื™ืช-ื›ืคื™ื™ืชื™ืช.
ื–ื” ืชื™ื›ืฃ ื™ื”ื™ื” ื‘ืจื•ืจ ืขื“ ืื™ืžื”. ืชืขืงื‘ื• ืื—ืจื™.
07:15
This is going to become really freaking obvious. Just go with me.
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07:18
(Laughter)
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(ืฆื—ื•ืง)
07:19
So what I did was I sorted all this stuff by zip code.
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ืžื™ื™ื ืชื™ ืืช ื›ืœ ื–ื” ืœืคื™ ืื–ื•ืจื™ ืžื™ืงื•ื“
07:23
And I looked at word analysis.
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ื•ื‘ื™ืฆืขืชื™ ื ื™ืชื•ื— ืžืœื™ื.
07:25
These are some dating profiles from 2010
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ืืœื” ื”ื ื›ืžื” ืคืจื•ืคื™ืœื™ ื”ื›ืจื•ื™ื•ืช ืž-2010
07:28
with the word "lonely" highlighted.
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ื›ืฉื”ืžื™ืœื” "ืœื‘ื“" ืžื•ื“ื’ืฉืช.
07:30
If you look at these things topographically,
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ืื ื”ื•ืคื›ื™ื ืืช ื–ื” ืœืžืคื”,
07:33
if you imagine dark colors to light colors are more use of the word,
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ื•ืžื“ืžื™ื™ื ื™ื ืฉืฆื‘ืขื™ื ื‘ื”ื™ืจื™ื ืžื™ื™ืฆื’ื™ื ืฉื™ืžื•ืฉ ืจื‘ ื‘ืžื™ืœื”,
07:36
you can see that Appalachia is a pretty lonely place.
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ืืคืฉืจ ืœืจืื•ืช ืฉื”ืจื™ ื”ืืคืœืฆ'ื™ื ื”ื ืžืงื•ื ื‘ื•ื“ื“ ืœืžื“ื™.
07:41
You can also see that Nebraska ain't that funny.
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ืจื•ืื™ื ื’ื...
ืฉื’ื ื‘ื ื‘ืจืกืงื” ืœื ื›ื™ืฃ. (ืฆื—ื•ืง)
07:48
This is the kinky map, so what this is showing you
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ื”ื ื” ื”ืžืคื” ืฉืœ ื”ืกื˜ื™ื•ืช. ืžื” ืฉืจื•ืื™ื ื‘ื” --
(ืฆื—ื•ืง)
ืจื•ืื™ื ื‘ื” ืฉืœื ืฉื™ื ื‘ืืœืกืงื” ื›ื“ืื™ ืœื™ืฆื•ืจ ืงืฉืจ
07:54
is that the women in Alaska need to get together
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07:57
with the men in southern New Mexico,
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ืขื ื’ื‘ืจื™ื ื‘ื“ืจื•ื ื ื™ื•-ืžืงืกื™ืงื• ื•ืœืขืฉื•ืช ื—ื™ื™ื.
07:58
and have a good time.
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08:00
And I have this at a pretty granular level,
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ื™ืจื“ืชื™ ื›ืืŸ ืœืจื–ื•ืœื•ืฆื™ื•ืช ื ืžื•ื›ื•ืช ืœืžื“ื™,
08:03
so I can tell you that the men in the eastern half of Long Island
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ืื– ืื ื™ ื™ื›ื•ืœ ืœื’ืœื•ืช ืœื›ื ืฉื”ื’ื‘ืจื™ื ื‘ื—ืฆื™ ื”ืžื–ืจื—ื™ ืฉืœ ืœื•ื ื’ ืื™ื™ืœื ื“
08:06
are way more interested in being spanked
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ืžืขื•ื ื™ื™ื ื™ื ื”ืจื‘ื” ื™ื•ืชืจ ืœืงื‘ืœ ื”ืฆืœืคื•ืช
08:08
than men in the western half of Long Island.
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ืžื’ื‘ืจื™ื ื‘ื—ืฆื™ ื”ืžืขืจื‘ื™ ืฉืœ ืœื•ื ื’ ืื™ื™ืœื ื“.
(ืฆื—ื•ืง)
08:11
This will be your one takeaway from this whole conference.
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ื–ื” ื™ื”ื™ื” ื”ืœืงื— ื”ื›ื™ ื—ืฉื•ื‘ ืฉืœื›ื ืžื›ืœ ื”ื›ื ืก.
08:14
You're going to remember that fact for, like, 30 years.
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ืืชื ืชื–ื›ืจื• ืืช ื”ืขื•ื‘ื“ื” ื”ื–ืืช ืœืžืฉืš 30 ืฉื ื”.
08:17
(Laughter)
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(ืฆื—ื•ืง) ืื ื™ ืžื‘ื˜ื™ื— ืœื›ื.
08:20
When you bring this down to a cartographic level,
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ื›ืฉืขื•ื‘ืจื™ื ืœืจืžื” ื”ืงืจื˜ื•ื’ืจืคื™ืช,
ืืคืฉืจ ืœืฉืจื˜ื˜ ืžืคื•ืช ื•ืœืขืฉื•ืช ืืช ืžื” ืฉืขืฉื™ืชื™ ืขื ื‘ื“ื™ืงื•ืช ื”ืจืื™ื™ื”.
08:23
you can make maps and do the same trick I was doing with the eye charts.
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ื‘ืžืงื•ื ืฉืžื” ืฉืœ ื›ืœ ืขื™ืจ ื‘ืืจื”"ื‘ ืืคืฉืจ ืœื”ื›ื ื™ืก
08:26
You can replace the name of every city in the United States
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ืืช ื”ืžื™ืœื” ืฉื‘ื” ืžืฉืชืžืฉื™ื ืฉื ื™ื•ืชืจ ืžื‘ื›ืœ ืžืงื•ื ืื—ืจ.
08:29
with the word people use more in that city than anywhere else.
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ืื ืื™-ืคืขื ื™ืฆืืชื ืขื ืžื™ืฉื”ื• ืžืกื™ืื˜ืœ,
08:32
If you've ever dated anyone from Seattle, this makes perfect sense.
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ื–ื” ื ืจืื” ื”ื’ื™ื•ื ื™ ืœื’ืžืจื™.
08:35
You've got "pretty." You've got "heartbreak."
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ื”ื ื” ื”ืžืœื™ื "ื™ืคื”", "ืฉื‘ืจื•ืŸ ืœื‘", "ื”ื•ืคืขื”", "ืกื™ื’ืจื™ื”".
08:38
You've got "gig." You've got "cigarette."
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08:40
They play in a band and they smoke.
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ืžื ื’ื ื™ื ืฉื ื‘ืœื”ืงื•ืช ื•ืžืขืฉื ื™ื.
08:43
And right above that you can see "email."
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ื•ืžืžืฉ ืžืขืœ ื–ื” ืืคืฉืจ ืœืจืื•ืช ืืช ื”ืžื™ืœื” ื“ื•ื"ืœ.
08:45
That's Redmond, Washington,
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ื–ืืช ืจื“ืžื•ื ื“ ืฉื‘ื•ื•ืฉื™ื ื’ื˜ื•ืŸ, ื”ืžื˜ื” ืฉืœ ืชืื’ื™ื“ ืžื™ืงืจื•ืกื•ืคื˜.
08:46
which is the headquarters of the Microsoft Corporation.
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ื—ืœืง ืžื”ืžืœื™ื ืžื•ื‘ื ื•ืช ืžืืœื™ื”ืŸ:
08:49
Some of these you can guess -- so, Los Angeles is "acting"
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ืœื•ืก-ืื ื’'ืœืก ื”ื™ื "ืžืฉื—ืง" ื•ืกืŸ-ืคืจื ืฆื™ืกืงื• ื”ื™ื "ื’ื™ื™".
08:52
and San Francisco is "gay."
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ื›ืžื” ืžื”ืŸ ืงืฆืช ื™ื•ืชืจ ืขืฆื•ื‘ื•ืช.
08:54
Some are a little bit more heartbreaking.
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ื‘ื‘ืื˜ื•ืŸ ืจื•ื’' ืžื“ื‘ืจื™ื ืขืœ "ื—ืžื•ืงื™ื";
08:56
In Baton Rouge, they talk about being curvy;
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ืœืžื˜ื”, ื‘ื ื™ื•-ืื•ืจืœื™ื ืก, ืขื“ื™ื™ืŸ ืžื“ื‘ืจื™ื ืขืœ ื”ืฉื˜ืคื•ืŸ.
08:58
downstream in New Orleans, they still talk about the flood.
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ื‘ื‘ื™ืจืช ืืžืจื™ืงื” ืื ืฉื™ื ืขื“ื™ื™ืŸ ืื•ืžืจื™ื ืฉื”ื "ืžืขื ื™ื™ื ื™ื".
09:01
Folks in the American capital will say they're interesting.
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09:03
People in Baltimore, Maryland, will say they're afraid.
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ื‘ื‘ืœื˜ื™ืžื•ืจ ืฉื‘ืžืจื™ืœื ื“ ื”ื ืื•ืžืจื™ื ืฉื”ื ืคื•ื—ื“ื™ื.
09:06
This is New Jersey.
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ื–ืืช ื ื™ื•-ื’'ืจื–ื™.
09:08
I grew up somewhere between "annoying" and "cynical."
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ืื ื™ ื’ื“ืœืชื™ ืื™ืคืฉื”ื• ื‘ื™ืŸ "ืžืขืฆื‘ืŸ" ืœ"ืฆื™ื ื™".
09:10
(Laughter) (Applause)
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(ืฆื—ื•ืง) (ืžื—ื™ืื•ืช ื›ืคื™ื™ื)
09:15
And New York City's number one word is "now,"
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ื•ื‘ืขื™ืจ ื ื™ื•-ื™ื•ืจืง ื”ืžื™ืœื” ืžืก' 1 ื”ื™ื "ื›ืจื’ืข",
09:17
as in, "Now I'm working as a waiter, but actually I'm an actor."
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ื›ืžื• ื‘"ื›ืจื’ืข ืื ื™ ืขื•ื‘ื“ ื›ืกื•ืคืจ, ืื‘ืœ ื‘ืขืฆื ืื ื™ ืฉื—ืงืŸ."
09:21
(Laughter)
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(ืฆื—ื•ืง)
09:22
Or, "Now I'm a professor of engineering at NYU, but actually I'm an artist."
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ืื• "ื›ืจื’ืข ืื ื™ ืžืจืฆื” ืœื”ื ื“ืกื” ื‘ืื•ื ื™ื‘ืจืกื™ื˜ืช ื ื™ื•-ื™ื•ืจืง, ืื‘ืœ ื‘ืขืฆื ืื ื™ ืืžืŸ".
09:26
If you go upstate, you see "dinosaur."
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ืื ืžืžืฉื™ื›ื™ื ืฆืคื•ื ื”, ืจื•ืื™ื "ื“ื™ื ื•ื–ืื•ืจ": ื–ืืช ืกื™ืจืงื™ื•ื–.
09:28
That's Syracuse.
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ื”ืื•ื›ืœ ื”ื›ื™ ื˜ื•ื‘ ื‘ืกื™ืจืงื™ื•ื– ืฉื‘ืžื“ื™ื ืช ื ื™ื•-ื™ื•ืจืง,
09:29
The best place to eat in Syracuse, New York,
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09:31
is a Hell's Angels barbecue joint called Dinosaur Barbecue.
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ื”ื•ื ื‘ืžืื•ืจืช ื‘ืจื‘ื™ืงื™ื• ืฉืœ ืžืœืื›ื™ ื”ืฉื˜ืŸ ื‘ืฉื "ื“ื™ื ื•ื–ืื•ืจ ืขืœ ื”ืืฉ".
09:34
That's where you would take somebody on a date.
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ืœืฉื ืœื•ืงื—ื™ื ืžื™ืฉื”ื• ืœื‘ื™ืœื•ื™.
09:36
I live somewhere between "unconditional" and "midsummer," in Midtown Manhattan.
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ืื ื™ ื’ืจ ืื™ืคืฉื”ื• ื‘ื™ืŸ "ืœืœื ืชื ืื™ื" ืœ"ืืžืฆืข ื”ืงื™ืฅ", ื‘ืœื‘ ืžื ื”ื˜ืŸ.
09:40
And this is gentrified North Brooklyn,
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ื–ืืช ืฆืคื•ืŸ ื‘ืจื•ืงืœื™ืŸ ื”ืžื—ื•ื“ืฉืช,
09:42
so you've got "DJ" and "glamorous" and "hipsters" and "urbane."
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ืื– ื™ืฉ ืœื›ื "ืชืงืœื™ื˜ืŸ", "ื–ื•ื”ืจ", "ื”ื™ืคืกื˜ืจ" ื•"ืื•ืจื‘ื ื™".
ืื– ืื•ืœื™ ื–ื” ื“ื™ื•ืงืŸ ื“ืžื•ืงืจื˜ื™ ื™ื•ืชืจ, ื ื›ื•ืŸ?
09:46
So that's maybe a more democratic portrait.
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09:48
And the idea was, what if we made red-state and blue-state maps
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ื”ืจืขื™ื•ืŸ ื”ื™ื” ืœื‘ื“ื•ืง ืžื” ื™ืงืจื” ืื ื ืžืคื” ืžื“ื™ื ื•ืช ื‘ืื“ื•ื ื•ื‘ื›ื—ื•ืœ
09:51
based on what we want to do on a Friday night?
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ืœืคื™ ืžื” ืฉืžืชื—ืฉืง ืœื ื• ืœืขืฉื•ืช ื‘ืขืจื‘ ืฉื™ืฉื™.
09:53
This is a self-portrait.
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ื–ื”ื• ื“ื™ื•ืงืŸ ืขืฆืžื™.
09:55
This is based on my email,
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ื”ื•ื ืžื‘ื•ืกืก ืขืœ ื”ื“ื•ื"ืœ ืฉืœื™,
ื›-500,000 ืžื›ืชื‘ื™ ื“ื•ื"ืœ ืฉื ืฉืœื—ื• ื‘ืžืฉืš 20 ืฉื ื”.
09:57
about 500,000 emails sent over 20 years.
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ืชื•ื›ืœื• ืœื—ืฉื•ื‘ ืขืœ ื–ื” ื›ืขืœ ืกื™ื›ื•ื ืฉืœ ืฆื™ืœื•ืžื™ "ืกืœืคื™".
10:00
You can think of this as a quantified selfie.
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10:03
So what I'm doing is running a physics equation
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ืื ื™ ืžืจื™ืฅ ืžืฉื•ื•ืืช ืคื™ื–ื™ืงื” ืขืœ ื™ืกื•ื“ ื”ื ืชื•ื ื™ื ื”ืื™ืฉื™ื™ื ืฉืœื™.
10:06
based on my personal data.
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10:07
You have to imagine everybody I've ever corresponded with.
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ื–ื” ืžืชืืจ ืืช ื›ืœ ืžื™ ืฉื”ืชื›ืชื‘ืชื™ ืื™ืชื•,
10:10
It started out in the middle and it exploded with a big bang.
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ื–ื” ื”ืชื—ื™ืœ ื‘ืžืจื›ื– ื•ื”ืชืคืฉื˜ ื›ืžืคืฅ ื’ื“ื•ืœ,
10:13
And everybody has gravity to one another,
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ื•ื‘ื™ืŸ ื›ื•ืœื ืคื•ืขืœืช ืžืขื™ืŸ ื›ื‘ื™ื“ื”
10:15
gravity based on how much they've been emailing,
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ื”ืžื‘ื•ืกืกืช ืขืœ ื›ืžื•ืช ื”ื“ื•ื"ืœ ื‘ื™ื ื™ื”ื,
10:18
who they've been emailing with.
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ืขื ืžื™ ื”ื ื”ืชื›ืชื‘ื•.
10:19
And it also does sentimental analysis,
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ื•ื–ื” ื’ื ืžื‘ืฆืข ื ื™ืชื•ื— ืจื’ืฉื ื•ืช.
10:21
so if I say "I love you," you're heavier to me.
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ืื ืื ื™ ืื•ืžืจ "ืื ื™ ืื•ื”ื‘ ืื•ืชืš", ื™ืฉ ืœืื•ืชื• ืื“ื ื™ื•ืชืจ ื›ื‘ื™ื“ื”
10:23
And you attract to my email addresses in the middle,
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ื•ื”ื•ื ื ืžืฉืš ืืœ ื›ืชื•ื‘ื•ืช ื”ื“ื•ื"ืœ ืฉืœื™, ื‘ืžืจื›ื–,
10:26
which act like mainline stars.
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ืฉืžืžืœืื•ืช ืชืคืงื™ื“ ืฉืœ ืฉืžืฉื•ืช ื‘ืžืขืจื›ืช.
10:28
And all the names are handwritten.
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ื•ื›ืœ ื”ืฉืžื•ืช ื›ืชื•ื‘ื™ื ื‘ื™ื“.
10:30
Sometimes you do this data and this work with real-time data
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ืœืคืขืžื™ื ืื ื™ ืขื•ืฉื” ืืช ื”ื™ืฆื™ืจื” ื”ื–ืืช ืขื ื ืชื•ื ื™ ื–ืžืŸ-ืืžืช,
10:34
to illuminate a specific problem in a specific city.
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ื›ื“ื™ ืœื”ื“ื’ื™ืฉ ื‘ืขื™ื” ืžืกื•ื™ืžืช ื‘ืขื™ืจ ืžืกื•ื™ืžืช.
10:38
This is a Walther PPK 9mm semiautomatic handgun
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ื–ื”ื• ืืงื“ื— ื—ืฆื™-ืื•ื˜ื•ืžื˜ื™ ืžืกื•ื’ ื•ื•ืœื˜ืจ ืคื™-ืคื™-ืงื™ื™
10:40
that was used in a shooting in the French Quarter of New Orleans
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ืฉืฉื™ืžืฉ ื‘ืื™ืจื•ืข ื™ืจื™ ื‘ืจื•ื‘ืข ื”ืฆืจืคืชื™ ืฉืœ ื ื™ื•-ืื•ืจืœื™ื ืก
10:43
about two years ago on Valentine's Day in an argument over parking.
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ืœืคื ื™ ื›ืฉื ืชื™ื™ื, ื‘ื™ื•ื ื”ืื”ื‘ื”, ื‘ื•ื™ื›ื•ื— ื‘ืงืฉืจ ืœืžืงื•ื ื—ื ื™ื”.
ืืœื” ื”ืกื™ื’ืจื™ื•ืช ืฉืœื™.
10:47
Those are my cigarettes.
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10:48
This is the house where the shooting took place.
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ื–ื” ื”ื‘ื™ืช ืฉื‘ื• ืื™ืจืข ื”ื™ืจื™.
10:50
This project involved a little bit of engineering.
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ื”ืžื™ื–ื ื”ื–ื” ื“ืจืฉ ืžืขื˜ ืžืœืื›ืช ื”ื ื“ืกื”.
ื—ื™ื‘ืจืชื™ ืฉืจืฉืจืช ืื•ืคื ื™ื™ื ืœื’ืœ ืืจื›ื•ื‘ื” ืฉื”ื•ื ืข ื‘ื‘ืงืจื” ืฉืœ ืžื—ืฉื‘.
10:53
I've got a bike chain rigged up as a cam shaft,
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10:55
with a computer driving it.
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10:56
That computer and the mechanism are buried in a box.
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ื”ืžื—ืฉื‘ ื•ื”ืžื ื’ื ื•ืŸ ื˜ืžื•ื ื™ื ื‘ืชื™ื‘ื”.
10:59
The gun's on top welded to a steel plate.
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ื”ืืงื“ื— ืฉืœืžืขืœื” ืžื•ืœื—ื ืœืœื•ื— ืคืœื“ื”, ืœื”ื“ืง ืžื—ื•ื‘ืจ ื—ื•ื˜ ืชื™ืœ
11:01
There's a wire going through to the trigger,
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11:04
and the computer in the box is online.
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ื•ื”ืžื—ืฉื‘ ืฉื‘ืชื™ื‘ื” ืžื—ื•ื‘ืจ ืœืจืฉืช ื”ืงืฉืจ ืฉืœ ืžืฉื˜ืจืช ื ื™ื•-ืื•ืจืœื™ื ืก
11:06
It's listening to the 911 feed of the New Orleans Police Department,
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11:09
so that anytime there's a shooting reported in New Orleans,
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ื›ืš ืฉืขื ื›ืœ ื“ื™ื•ื•ื— ืขืœ ื™ืจื™ ื‘ื ื™ื•-ืื•ืจืœื™ื ืก...
11:12
(Gunshot sound)
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(ืงื•ืœ ื™ืจื™ ืืงื“ื—) ื”ืืงื“ื— ื™ื•ืจื”.
11:13
the gun fires.
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11:15
Now, there's a blank, so there's no bullet.
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ื–ื”ื• ื›ื“ื•ืจ ืกืจืง, ืœื ืงืœื™ืข ืืžื™ืชื™.
11:18
There's big light, big noise
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ื™ืฉ ื”ื‘ื–ืง ืื•ืจ ื’ื“ื•ืœ, ื”ืจื‘ื” ืจืขืฉ,
11:20
and most importantly, there's a casing.
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ื•ื”ื›ื™ ื—ืฉื•ื‘ - ื ืคืœื˜ ืชืจืžื™ืœ.
11:22
There's about five shootings a day in New Orleans,
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ื‘ื ื™ื•-ืื•ืจืœื™ื ืก ื™ืฉ ื›-5 ืื™ืจื•ืขื™ ื™ืจื™ ื‘ื™ื•ื.
11:24
so over the four months this piece was installed,
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ืื– ื‘ืžืฉืš ืืจื‘ืขืช ื”ื—ื•ื“ืฉื™ื ืžืื– ืฉื”ื•ืชืงื ื” ื”ื™ืฆื™ืจื” ื”ื–ืืช,
ื”ืชื™ื‘ื” ื”ืชืžืœืื” ืชืจืžื™ืœื™ื.
11:27
the case filled up with bullets.
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11:29
You guys know what this is -- you call this "data visualization."
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ืืชื ืžื›ื™ืจื™ื ืืช ื–ื”. ื–ืืช "ื”ืžื—ืฉืช ื ืชื•ื ื™ื."
11:34
When you do it right, it's illuminating.
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ื›ืฉืขื•ืฉื™ื ืืช ื–ื” ื ื›ื•ืŸ, ื–ื” ืžืื™ืจ ืขื™ื ื™ื™ื.
11:36
When you do it wrong, it's anesthetizing.
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ื›ืฉืขื•ืฉื™ื ืืช ื–ื” ืœื-ื ื›ื•ืŸ, ื–ื” ืžืงื”ื” ืืช ื”ื—ื•ืฉื™ื.
11:39
It reduces people to numbers.
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ื–ื” ื”ื•ืคืš ื‘ื ื™-ืื“ื ืœืžืกืคืจื™ื.
11:41
So watch out.
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ืื– ืชื™ื–ื”ืจื•.
11:44
One last piece for you.
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ื™ืฆื™ืจื” ืื—ืจื•ื ื”.
11:46
I spent the last summer as the artist in residence
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ื‘ืงื™ืฅ ื”ืื—ืจื•ืŸ ื”ื™ื™ืชื™ ืืžืŸ ื”ื‘ื™ืช ืฉืœ ื›ื™ื›ืจ ื˜ื™ื™ืžืก.
11:49
for Times Square.
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11:50
And Times Square in New York is literally the crossroads of the world.
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ื•ื›ื™ื›ืจ ื˜ื™ื™ืžืก ื‘ื ื™ื•-ื™ื•ืจืง ื”ื™ื ื‘ืคื™ืจื•ืฉ ื”ืฆื•ืžืช ื”ืขื•ืœืžื™ืช.
11:54
One of the things people don't notice about it
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ื•ืื—ื“ ื”ื“ื‘ืจื™ื ืฉืœื ื™ื•ื“ืขื™ื ืขืœื™ื”,
11:56
is it's the most Instagrammed place on Earth.
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ื”ื•ื ืฉื–ื” ื”ืืชืจ ืฉืžืฆื•ืœื ื‘ืื™ื ื˜ืจื ื˜ ื”ื›ื™ ื”ืจื‘ื” ื‘ืขื•ืœื.
11:59
About every five seconds, someone commits a selfie
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ื‘ืขืจืš ื›ืœ 5 ืฉื ื™ื•ืช ืžื™ืฉื”ื• ืžื‘ืฆืข "ืกืœืคื™" ื‘ื›ื™ื›ืจ ื˜ื™ื™ืžืก.
12:02
in Times Square.
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12:04
That's 17,000 a day, and I have them all.
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ืžื“ื•ื‘ืจ ื‘-17,000 ื‘ื™ื•ื, ื•ื›ื•ืœื ืืฆืœื™.
12:07
(Laughter)
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(ืฆื—ื•ืง)
12:08
These are some of them with their eyes centered.
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ื”ื ื” ื›ืžื” ืžื”ื, ื›ืฉื”ืขื™ื ื™ื™ื ืžืžื•ืจื›ื–ื•ืช.
ื›ืœ ืชืจื‘ื•ืช ืชืฉืชืžืฉ ื‘ืžื™ืจื‘ ื”ื˜ื›ื ื•ืœื•ื’ื™ื” ืฉืขื•ืžื“ืช ืœืจืฉื•ืชื” ื›ื“ื™ ืœื™ืฆื•ืจ ืืžื ื•ืช.
12:11
Every civilization,
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12:12
will use the maximum level of technology available to make art.
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12:15
And it's the responsibility of the artist to ask questions
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ื•ืื—ืจื™ื•ืชื• ืฉืœ ื”ืืžืŸ ื”ื™ื ืœืขื•ืจืจ ืฉืืœื•ืช ืœื’ื‘ื™ ืžืฉืžืขื•ืชื” ืฉืœ ื”ื˜ื›ื ื•ืœื•ื’ื™ื” ื”ื–ืืช
12:17
about what that technology means
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12:19
and how it reflects our culture.
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ื•ืื™ืš ื”ื™ื ืžืฉืงืคืช ืืช ืชืจื‘ื•ืชื ื•.
12:21
So I leave you with this: we're more than numbers.
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ืื– ืชื—ืฉื‘ื• ืขืœ ื–ื”: ืื ื• ื™ื•ืชืจ ืžืืฉืจ ืžืกืคืจื™ื.
ืื ื• ื‘ื ื™-ืื“ื, ื•ื™ืฉ ืœื ื• ื—ืœื•ืžื•ืช ื•ืจืขื™ื•ื ื•ืช.
12:24
We're people, and we have dreams and ideas.
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12:26
And reducing us to statistics is something that's done
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ื•ื”ื”ื•ืจื“ื” ืฉืœื ื• ืœืžื“ืจื’ืช ื ืชื•ื ื™ื
ืžืกื›ื ืช ืื•ืชื ื•.
12:29
at our peril.
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12:30
Thank you very much.
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ืชื•ื“ื” ืจื‘ื” ืœื›ื.
12:31
(Applause)
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(ืžื—ื™ืื•ืช ื›ืคื™ื™ื)
ืขืœ ืืชืจ ื–ื”

ืืชืจ ื–ื” ื™ืฆื™ื’ ื‘ืคื ื™ื›ื ืกืจื˜ื•ื ื™ YouTube ื”ืžื•ืขื™ืœื™ื ืœืœื™ืžื•ื“ ืื ื’ืœื™ืช. ืชื•ื›ืœื• ืœืจืื•ืช ืฉื™ืขื•ืจื™ ืื ื’ืœื™ืช ื”ืžื•ืขื‘ืจื™ื ืขืœ ื™ื“ื™ ืžื•ืจื™ื ืžื”ืฉื•ืจื” ื”ืจืืฉื•ื ื” ืžืจื—ื‘ื™ ื”ืขื•ืœื. ืœื—ืฅ ืคืขืžื™ื™ื ืขืœ ื”ื›ืชื•ื‘ื™ื•ืช ื‘ืื ื’ืœื™ืช ื”ืžื•ืฆื’ื•ืช ื‘ื›ืœ ื“ืฃ ื•ื™ื“ืื• ื›ื“ื™ ืœื”ืคืขื™ืœ ืืช ื”ืกืจื˜ื•ืŸ ืžืฉื. ื”ื›ืชื•ื‘ื™ื•ืช ื’ื•ืœืœื•ืช ื‘ืกื ื›ืจื•ืŸ ืขื ื”ืคืขืœืช ื”ื•ื•ื™ื“ืื•. ืื ื™ืฉ ืœืš ื”ืขืจื•ืช ืื• ื‘ืงืฉื•ืช, ืื ื ืฆื•ืจ ืื™ืชื ื• ืงืฉืจ ื‘ืืžืฆืขื•ืช ื˜ื•ืคืก ื™ืฆื™ืจืช ืงืฉืจ ื–ื”.

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