ABOUT THE SPEAKER
Jonathan Harris - Artist, storyteller, Internet anthropologist
Artist and computer scientist Jonathan Harris makes online art that captures the world's expression -- and gives us a glimpse of the soul of the Internet.

Why you should listen

Brooklyn-based artist Jonathan Harris' work celebrates the world's diversity even as it illustrates the universal concerns of its occupants. His computer programs scour the Internet for unfiltered content, which his beautiful interfaces then organize to create coherence from the chaos.

His projects are both intensely personal (the "We Feel Fine" project, made with Sep Kanvar, which scans the world's blogs to collect snapshots of the writers' feelings) and entirely global (the new "Universe," which turns current events into constellations of words). But their effect is the same -- to show off a world that resonates with shared emotions, concerns, problems, triumphs and troubles.

More profile about the speaker
Jonathan Harris | Speaker | TED.com
TED2007

Jonathan Harris: The web as art

Filmed:
910,598 views

At the EG conference in December 2007, artist Jonathan Harris discusses his latest projects, which involve collecting stories: his own, strangers', and stories collected from the Internet, including his amazing "We Feel Fine."
- Artist, storyteller, Internet anthropologist
Artist and computer scientist Jonathan Harris makes online art that captures the world's expression -- and gives us a glimpse of the soul of the Internet. Full bio

Double-click the English transcript below to play the video.

00:16
So I'm going to talk today about collecting stories
0
0
4000
00:20
in some unconventional ways.
1
4000
2000
00:22
This is a picture of me from a very awkward stage in my life.
2
6000
4000
00:26
You might enjoy the awkwardly tight, cut-off pajama bottoms with balloons.
3
10000
5000
00:31
Anyway, it was a time when I was mainly interested
4
15000
2000
00:33
in collecting imaginary stories.
5
17000
2000
00:35
So this is a picture of me
6
19000
2000
00:37
holding one of the first watercolor paintings I ever made.
7
21000
2000
00:39
And recently I've been much more interested in collecting stories
8
23000
3000
00:42
from reality -- so, real stories.
9
26000
2000
00:44
And specifically, I'm interested in collecting my own stories,
10
28000
4000
00:48
stories from the Internet, and then recently, stories from life,
11
32000
3000
00:51
which is kind of a new area of work that I've been doing recently.
12
35000
4000
00:55
So I'll be talking about each of those today.
13
39000
2000
00:57
So, first of all, my own stories. These are two of my sketchbooks.
14
41000
3000
01:00
I have many of these books,
15
44000
2000
01:02
and I've been keeping them for about the last eight or nine years.
16
46000
2000
01:04
They accompany me wherever I go in my life,
17
48000
2000
01:06
and I fill them with all sorts of things,
18
50000
2000
01:08
records of my lived experience:
19
52000
2000
01:10
so watercolor paintings, drawings of what I see,
20
54000
4000
01:14
dead flowers, dead insects, pasted ticket stubs, rusting coins,
21
58000
4000
01:18
business cards, writings.
22
62000
3000
01:21
And in these books, you can find these short, little glimpses
23
65000
4000
01:25
of moments and experiences and people that I meet.
24
69000
2000
01:27
And, you know, after keeping these books for a number of years,
25
71000
3000
01:30
I started to become very interested in collecting
26
74000
2000
01:32
not only my own personal artifacts,
27
76000
2000
01:34
but also the artifacts of other people.
28
78000
2000
01:36
So, I started collecting found objects.
29
80000
2000
01:38
This is a photograph I found lying in a gutter in New York City
30
82000
2000
01:40
about 10 years ago.
31
84000
2000
01:42
On the front, you can see the tattered black-and-white photo of a woman's face,
32
86000
3000
01:45
and on the back it says, "To Judy, the girl with the Bill Bailey voice.
33
89000
4000
01:49
Have fun in whatever you do."
34
93000
2000
01:51
And I really loved this idea of the partial glimpse into somebody's life.
35
95000
3000
01:54
As opposed to knowing the whole story, just knowing a little bit of the story,
36
98000
3000
01:57
and then letting your own mind fill in the rest.
37
101000
2000
01:59
And that idea of a partial glimpse is something
38
103000
2000
02:01
that will come back in a lot of the work I'll be showing later today.
39
105000
3000
02:04
So, around this time I was studying computer science at Princeton University,
40
108000
3000
02:07
and I noticed that it was suddenly possible
41
111000
3000
02:10
to collect these sorts of personal artifacts,
42
114000
2000
02:12
not just from street corners, but also from the Internet.
43
116000
3000
02:15
And that suddenly, people, en masse, were leaving scores and scores
44
119000
4000
02:19
of digital footprints online that told stories of their private lives.
45
123000
4000
02:23
Blog posts, photographs, thoughts, feelings, opinions,
46
127000
4000
02:27
all of these things were being expressed by people online,
47
131000
2000
02:29
and leaving behind trails.
48
133000
2000
02:31
So, I started to write computer programs
49
135000
2000
02:33
that study very, very large sets of these online footprints.
50
137000
3000
02:36
One such project is about a year and a half old.
51
140000
2000
02:38
It's called "We Feel Fine."
52
142000
2000
02:40
This is a project that scans the world's newly posted blog entries
53
144000
3000
02:43
every two or three minutes, searching for occurrences of the phrases
54
147000
3000
02:46
"I feel" and "I am feeling." And when it finds one of those phrases,
55
150000
4000
02:50
it grabs the full sentence up to the period
56
154000
2000
02:52
and also tries to identify demographic information about the author.
57
156000
3000
02:55
So, their gender, their age, their geographic location
58
159000
3000
02:58
and what the weather conditions were like when they wrote that sentence.
59
162000
3000
03:01
It collects about 20,000 such sentences a day
60
165000
2000
03:03
and it's been running for about a year and a half,
61
167000
2000
03:05
having collected over 10 and a half million feelings now.
62
169000
3000
03:08
This is, then, how they're presented.
63
172000
2000
03:10
These dots here represent some of the English-speaking world's
64
174000
3000
03:13
feelings from the last few hours,
65
177000
3000
03:16
each dot being a single sentence stated by a single blogger.
66
180000
3000
03:19
And the color of each dot corresponds to the type of feeling inside,
67
183000
3000
03:22
so the bright ones are happy, and the dark ones are sad.
68
186000
3000
03:25
And the diameter of each dot corresponds
69
189000
2000
03:27
to the length of the sentence inside.
70
191000
2000
03:29
So the small ones are short, and the bigger ones are longer.
71
193000
3000
03:32
"I feel fine with the body I'm in, there'll be no easy excuse
72
196000
2000
03:34
for why I still feel uncomfortable being close to my boyfriend,"
73
198000
4000
03:38
from a twenty-two-year-old in Japan.
74
202000
2000
03:40
"I got this on some trading locally,
75
204000
2000
03:42
but really don't feel like screwing with wiring and crap."
76
206000
2000
03:44
Also, some of the feelings contain photographs in the blog posts.
77
208000
3000
03:47
And when that happens, these montage compositions are automatically created,
78
211000
5000
03:52
which consist of the sentence and images being combined.
79
216000
3000
03:55
And any of these can be opened up to reveal the sentence inside.
80
219000
4000
03:59
"I feel good."
81
223000
5000
04:04
"I feel rough now, and I probably gained 100,000 pounds,
82
228000
3000
04:07
but it was worth it."
83
231000
4000
04:11
"I love how they were able to preserve most in everything
84
235000
3000
04:14
that makes you feel close to nature -- butterflies,
85
238000
2000
04:16
man-made forests, limestone caves and hey, even a huge python."
86
240000
5000
04:21
So the next movement is called mobs.
87
245000
2000
04:23
This provides a slightly more statistical look at things.
88
247000
2000
04:25
This is showing the world's most common feelings overall right now,
89
249000
3000
04:28
dominated by better, then bad, then good, then guilty, and so on.
90
252000
3000
04:31
Weather causes the feelings to assume the physical traits
91
255000
3000
04:34
of the weather they represent. So the sunny ones swirl around,
92
258000
2000
04:36
the cloudy ones float along, the rainy ones fall down,
93
260000
3000
04:39
and the snowy ones flutter to the ground.
94
263000
2000
04:41
You can also stop a raindrop and open the feeling inside.
95
265000
6000
04:47
Finally, location causes the feelings to move to their spots
96
271000
2000
04:49
on a world map, giving you a sense of their geographic distribution.
97
273000
3000
04:52
So I'll show you now some of my favorite montages from "We Feel Fine."
98
276000
3000
04:55
These are the images that are automatically constructed.
99
279000
2000
04:57
"I feel like I'm diagonally parked in a parallel universe."
100
281000
3000
05:00
(Laughter)
101
284000
3000
05:03
"I've kissed numerous other boys and it hasn't felt good,
102
287000
2000
05:05
the kisses felt messy and wrong,
103
289000
2000
05:07
but kissing Lucas feels beautiful and almost spiritual."
104
291000
6000
05:13
"I can feel my cancer grow."
105
297000
3000
05:16
"I feel pretty."
106
300000
3000
05:19
"I feel skinny, but I'm not."
107
303000
3000
05:22
"I'm 23, and a recovering meth and heroin addict,
108
306000
2000
05:24
and feel absolutely blessed to still be alive."
109
308000
3000
05:27
"I can't wait to see them racing for the first time at Daytona next month,
110
311000
3000
05:30
because I feel the need for speed."
111
314000
2000
05:32
(Laughter)
112
316000
3000
05:35
"I feel sassy."
113
319000
1000
05:36
"I feel so sexy in this new wig."
114
320000
3000
05:39
As you can see, "We Feel Fine" collects
115
323000
2000
05:41
very, very small-scale personal stories.
116
325000
2000
05:43
Sometimes, stories as short as two or three words.
117
327000
2000
05:45
So, really even challenging the notion
118
329000
2000
05:47
of what can be considered a story.
119
331000
2000
05:49
And recently, I've become interested in diving much more deeply into a single story.
120
333000
4000
05:53
And that's led me to doing some work with the physical world,
121
337000
3000
05:56
not with the Internet,
122
340000
1000
05:57
and only using the Internet at the very last moment, as a presentation medium.
123
341000
4000
06:01
So these are some newer projects that
124
345000
1000
06:02
actually aren't even launched publicly yet.
125
346000
2000
06:04
The first such one is called "The Whale Hunt."
126
348000
2000
06:06
Last May, I spent nine days living up in Barrow, Alaska,
127
350000
3000
06:09
the northernmost settlement in the United States,
128
353000
2000
06:11
with a family of Inupiat Eskimos,
129
355000
2000
06:13
documenting their annual spring whale hunt.
130
357000
3000
06:16
This is the whaling camp here, we're about six miles from shore,
131
360000
3000
06:19
camping on five and a half feet of thick, frozen pack ice.
132
363000
3000
06:22
And that water that you see there is the open lead,
133
366000
2000
06:24
and through that lead, bowhead whales migrate north each springtime.
134
368000
4000
06:28
And the Eskimo community basically camps out on the edge of the ice here,
135
372000
3000
06:31
waits for a whale to come close enough to attack. And when it does,
136
375000
3000
06:34
it throws a harpoon at it, and then hauls the whale up
137
378000
2000
06:36
under the ice, and cuts it up.
138
380000
2000
06:38
And that would provide the community's food supply for a long time.
139
382000
2000
06:40
So I went up there, and I lived with these guys
140
384000
2000
06:42
out in their whaling camp here, and photographed the entire experience,
141
386000
3000
06:45
beginning with the taxi ride to Newark airport in New York,
142
389000
4000
06:49
and ending with the butchering of the second whale, seven and a half days later.
143
393000
3000
06:52
I photographed that entire experience at five-minute intervals.
144
396000
3000
06:55
So every five minutes, I took a photograph.
145
399000
2000
06:57
When I was awake, with the camera around my neck.
146
401000
2000
06:59
When I was sleeping, with a tripod and a timer.
147
403000
2000
07:01
And then in moments of high adrenaline,
148
405000
2000
07:03
like when something exciting was happening,
149
407000
2000
07:05
I would up that photographic frequency to as many as
150
409000
2000
07:07
37 photographs in five minutes.
151
411000
2000
07:09
So what this created was a photographic heartbeat
152
413000
2000
07:11
that sped up and slowed down, more or less matching
153
415000
2000
07:13
the changing pace of my own heartbeat.
154
417000
3000
07:16
That was the first concept here.
155
420000
2000
07:18
The second concept was to use this experience to think about
156
422000
2000
07:20
the fundamental components of any story.
157
424000
2000
07:22
What are the things that make up a story?
158
426000
2000
07:24
So, stories have characters. Stories have concepts.
159
428000
3000
07:27
Stories take place in a certain area. They have contexts.
160
431000
2000
07:29
They have colors. What do they look like?
161
433000
2000
07:31
They have time. When did it take place? Dates -- when did it occur?
162
435000
3000
07:34
And in the case of the whale hunt, also this idea of an excitement level.
163
438000
3000
07:37
The thing about stories, though, in most of the existing mediums
164
441000
3000
07:40
that we're accustomed to -- things like novels, radio,
165
444000
3000
07:43
photographs, movies, even lectures like this one --
166
447000
2000
07:45
we're very accustomed to this idea of the narrator or the camera position,
167
449000
4000
07:49
some kind of omniscient, external body
168
453000
2000
07:51
through whose eyes you see the story.
169
455000
3000
07:54
We're very used to this.
170
458000
2000
07:56
But if you think about real life, it's not like that at all.
171
460000
2000
07:58
I mean, in real life, things are much more nuanced and complex,
172
462000
2000
08:00
and there's all of these overlapping stories
173
464000
2000
08:02
intersecting and touching each other.
174
466000
2000
08:04
And so I thought it would be interesting to build a framework
175
468000
3000
08:07
to surface those types of stories. So, in the case of "The Whale Hunt,"
176
471000
4000
08:11
how could we extract something like the story of Simeon and Crawford,
177
475000
3000
08:14
involving the concepts of wildlife, tools and blood, taking place on the Arctic Ocean,
178
478000
4000
08:18
dominated by the color red, happening around 10 a.m. on May 3,
179
482000
3000
08:21
with an excitement level of high?
180
485000
2000
08:23
So, how to extract this order of narrative from this larger story?
181
487000
5000
08:28
I built a web interface for viewing "The Whale Hunt" that attempts to do just this.
182
492000
5000
08:33
So these are all 3,214 pictures taken up there.
183
497000
4000
08:37
This is my studio in Brooklyn. This is the Arctic Ocean,
184
501000
4000
08:41
and the butchering of the second whale, seven days later.
185
505000
3000
08:44
You can start to see some of the story here, told by color.
186
508000
3000
08:47
So this red strip signifies the color of the wallpaper
187
511000
3000
08:50
in the basement apartment where I was staying.
188
514000
2000
08:52
And things go white as we move out onto the Arctic Ocean.
189
516000
3000
08:55
Introduction of red down here, when whales are being cut up.
190
519000
4000
08:59
You can see a timeline, showing you the exciting moments throughout the story.
191
523000
3000
09:02
These are organized chronologically.
192
526000
2000
09:04
Wheel provides a slightly more playful version of the same,
193
528000
3000
09:07
so these are also all the photographs organized chronologically.
194
531000
3000
09:10
And any of these can be clicked,
195
534000
2000
09:12
and then the narrative is entered at that position.
196
536000
2000
09:14
So here I am sleeping on the airplane heading up to Alaska.
197
538000
3000
09:17
That's "Moby Dick."
198
541000
2000
09:19
This is the food we ate.
199
543000
2000
09:21
This is in the Patkotak's family living room
200
545000
3000
09:24
in their house in Barrow. The boxed wine they served us.
201
548000
3000
09:27
Cigarette break outside -- I don't smoke.
202
551000
3000
09:30
This is a really exciting sequence of me sleeping.
203
554000
4000
09:34
This is out at whale camp, on the Arctic Ocean.
204
558000
4000
09:38
This graph that I'm clicking down here is meant to be
205
562000
2000
09:40
reminiscent of a medical heartbeat graph,
206
564000
2000
09:42
showing the exciting moments of adrenaline.
207
566000
5000
09:47
This is the ice starting to freeze over. The snow fence they built.
208
571000
3000
09:50
And so what I'll show you now is the ability to pull out sub-stories.
209
574000
3000
09:53
So, here you see the cast. These are all of the people in "The Whale Hunt"
210
577000
4000
09:57
and the two whales that were killed down here.
211
581000
2000
09:59
And we could do something as arbitrary as, say,
212
583000
2000
10:01
extract the story of Rony, involving the concepts of blood
213
585000
6000
10:07
and whales and tools, taking place on the Arctic Ocean,
214
591000
5000
10:12
at Ahkivgaq camp, with the heartbeat level of fast.
215
596000
4000
10:16
And now we've whittled down that whole story
216
600000
2000
10:18
to just 29 matching photographs,
217
602000
2000
10:20
and then we can enter the narrative at that position.
218
604000
2000
10:22
And you can see Rony cutting up the whale here.
219
606000
2000
10:24
These whales are about 40 feet long,
220
608000
2000
10:26
and weighing over 40 tons. And they provide the food source
221
610000
3000
10:29
for the community for much of the year.
222
613000
4000
10:33
Skipping ahead a bit more here, this is Rony on the whale carcass.
223
617000
5000
10:38
They use no chainsaws or anything; it's entirely just blades,
224
622000
3000
10:41
and an incredibly efficient process.
225
625000
2000
10:43
This is the guys on the rope, pulling open the carcass.
226
627000
3000
10:46
This is the muktuk, or the blubber, all lined up for community distribution.
227
630000
4000
10:50
It's baleen. Moving on.
228
634000
3000
10:53
So what I'm going to tell you about next
229
637000
2000
10:55
is a very new thing. It's not even a project yet.
230
639000
3000
10:58
So, just yesterday, I flew in here from Singapore, and before that,
231
642000
3000
11:01
I was spending two weeks in Bhutan, the small Himalayan kingdom
232
645000
4000
11:05
nestled between Tibet and India.
233
649000
2000
11:07
And I was doing a project there about happiness,
234
651000
3000
11:10
interviewing a lot of local people.
235
654000
2000
11:12
So Bhutan has this really wacky thing where they base
236
656000
6000
11:18
most of their high-level governmental decisions around the concept
237
662000
2000
11:20
of gross national happiness instead of gross domestic product,
238
664000
4000
11:24
and they've been doing this since the '70s.
239
668000
2000
11:26
And it leads to just a completely different value system.
240
670000
3000
11:29
It's an incredibly non-materialistic culture,
241
673000
2000
11:31
where people don't have a lot, but they're incredibly happy.
242
675000
3000
11:34
So I went around and I talked to people about some of these ideas.
243
678000
3000
11:37
So, I did a number of things. I asked people a number of set questions,
244
681000
3000
11:40
and took a number of set photographs,
245
684000
2000
11:42
and interviewed them with audio, and also took pictures.
246
686000
2000
11:44
I would start by asking people to rate their happiness
247
688000
2000
11:46
between one and 10, which is kind of inherently absurd.
248
690000
3000
11:49
And then when they answered, I would inflate that number of balloons
249
693000
3000
11:52
and give them that number of balloons to hold.
250
696000
2000
11:54
So, you have some really happy person holding 10 balloons,
251
698000
2000
11:56
and some really sad soul holding one balloon.
252
700000
4000
12:00
But you know, even holding one balloon is like, kind of happy.
253
704000
3000
12:03
(Laughter)
254
707000
2000
12:05
And then I would ask them a number of questions like
255
709000
2000
12:07
what was the happiest day in their life, what makes them happy.
256
711000
2000
12:09
And then finally, I would ask them to make a wish.
257
713000
3000
12:12
And when they made a wish, I would write their wish
258
716000
2000
12:14
onto one of the balloons and take a picture of them holding it.
259
718000
3000
12:17
So I'm going to show you now just a few brief snippets
260
721000
3000
12:20
of some of the interviews that I did, some of the people I spoke with.
261
724000
3000
12:23
This is an 11-year-old student.
262
727000
2000
12:25
He was playing cops and robbers with his friends, running around town,
263
729000
3000
12:28
and they all had plastic toy guns.
264
732000
2000
12:30
His wish was to become a police officer.
265
734000
3000
12:33
He was getting started early. Those were his hands.
266
737000
3000
12:36
I took pictures of everybody's hands,
267
740000
2000
12:38
because I think you can often tell a lot about somebody
268
742000
2000
12:40
from how their hands look. I took a portrait of everybody,
269
744000
3000
12:43
and asked everybody to make a funny face.
270
747000
3000
12:46
A 17-year-old student. Her wish was to have been born a boy.
271
750000
4000
12:50
She thinks that women have a pretty tough go of things in Bhutan,
272
754000
3000
12:53
and it's a lot easier if you're a boy.
273
757000
2000
13:01
A 28-year-old cell phone shop owner.
274
765000
2000
13:03
If you knew what Paro looked like, you'd understand
275
767000
2000
13:05
how amazing it is that there's a cell phone shop there.
276
769000
5000
13:10
He wanted to help poor people.
277
774000
2000
13:19
A 53-year-old farmer. She was chaffing wheat,
278
783000
3000
13:22
and that pile of wheat behind her
279
786000
2000
13:24
had taken her about a week to make.
280
788000
2000
13:26
She wanted to keep farming until she dies.
281
790000
4000
13:30
You can really start to see the stories told by the hands here.
282
794000
3000
13:33
She was wearing this silver ring that had the word "love" engraved on it,
283
797000
3000
13:36
and she'd found it in the road somewhere.
284
800000
3000
13:43
A 16-year-old quarry worker.
285
807000
2000
13:45
This guy was breaking rocks with a hammer in the hot sunlight,
286
809000
4000
13:49
but he just wanted to spend his life as a farmer.
287
813000
3000
13:59
A 21-year-old monk. He was very happy.
288
823000
5000
14:04
He wanted to live a long life at the monastery.
289
828000
3000
14:10
He had this amazing series of hairs growing out of a mole on the left side of his face,
290
834000
4000
14:14
which I'm told is very good luck.
291
838000
3000
14:17
He was kind of too shy to make a funny face.
292
841000
4000
14:21
A 16-year-old student.
293
845000
5000
14:26
She wanted to become an independent woman.
294
850000
2000
14:28
I asked her about that, and she said she meant
295
852000
1000
14:29
that she doesn't want to be married,
296
853000
2000
14:31
because, in her opinion, when you get married in Bhutan as a woman,
297
855000
3000
14:34
your chances to live an independent life kind of end,
298
858000
3000
14:37
and so she had no interest in that.
299
861000
2000
14:45
A 24-year-old truck driver.
300
869000
2000
14:47
There are these terrifyingly huge Indian trucks
301
871000
2000
14:49
that come careening around one-lane roads with two-lane traffic,
302
873000
4000
14:53
with 3,000-foot drop-offs right next to the road,
303
877000
3000
14:56
and he was driving one of these trucks.
304
880000
2000
14:58
But all he wanted was to just live a comfortable life, like other people.
305
882000
3000
15:08
A 24-year-old road sweeper. I caught her on her lunch break.
306
892000
3000
15:11
She'd built a little fire to keep warm, right next to the road.
307
895000
3000
15:14
Her wish was to marry someone with a car.
308
898000
4000
15:18
She wanted a change in her life.
309
902000
2000
15:20
She lives in a little worker's camp right next to the road,
310
904000
3000
15:23
and she wanted a different lot on things.
311
907000
2000
15:33
An 81-year-old itinerant farmer.
312
917000
2000
15:35
I saw this guy on the side of the road,
313
919000
2000
15:37
and he actually doesn't have a home.
314
921000
2000
15:39
He travels from farm to farm each day trying to find work,
315
923000
2000
15:41
and then he tries to sleep at whatever farm he gets work at.
316
925000
4000
15:45
So his wish was to come with me, so that he had somewhere to live.
317
929000
3000
15:55
He had this amazing knife that he pulled out of his gho
318
939000
2000
15:57
and started brandishing when I asked him to make a funny face.
319
941000
4000
16:01
It was all good-natured.
320
945000
2000
16:04
A 10-year-old.
321
948000
4000
16:08
He wanted to join a school and learn to read,
322
952000
2000
16:10
but his parents didn't have enough money to send him to school.
323
954000
4000
16:14
He was eating this orange, sugary candy
324
958000
2000
16:16
that he kept dipping his fingers into,
325
960000
2000
16:18
and since there was so much saliva on his hands,
326
962000
2000
16:20
this orange paste started to form on his palms.
327
964000
3000
16:27
(Laughter)
328
971000
2000
16:30
A 37-year-old road worker.
329
974000
3000
16:33
One of the more touchy political subjects in Bhutan
330
977000
4000
16:37
is the use of Indian cheap labor
331
981000
3000
16:40
that they import from India to build the roads,
332
984000
3000
16:43
and then they send these people home once the roads are built.
333
987000
2000
16:45
So these guys were in a worker's gang
334
989000
2000
16:47
mixing up asphalt one morning on the side of the highway.
335
991000
3000
16:50
His wish was to make some money and open a store.
336
994000
3000
17:00
A 75-year-old farmer. She was selling oranges on the side of the road.
337
1004000
4000
17:04
I asked her about her wish, and she said,
338
1008000
2000
17:06
"You know, maybe I'll live, maybe I'll die, but I don't have a wish."
339
1010000
3000
17:14
She was chewing betel nut, which caused her teeth
340
1018000
3000
17:17
over the years to turn very red.
341
1021000
2000
17:19
Finally, this is a 26-year-old nun I spoke to.
342
1023000
6000
17:25
Her wish was to make a pilgrimage to Tibet.
343
1029000
3000
17:28
I asked her how long she planned to live in the nunnery and she said,
344
1032000
2000
17:30
"Well, you know, of course, it's impermanent,
345
1034000
2000
17:32
but my plan is to live here until I'm 30, and then enter a hermitage."
346
1036000
4000
17:36
And I said, "You mean, like a cave?" And she said, "Yeah, like a cave."
347
1040000
5000
17:41
And I said, "Wow, and how long will you live in the cave?"
348
1045000
3000
17:44
And she said, "Well, you know,
349
1048000
2000
17:46
I think I'd kind of like to live my whole life in the cave."
350
1050000
4000
17:50
I just thought that was amazing. I mean, she spoke in a way --
351
1054000
2000
17:52
with amazing English, and amazing humor, and amazing laughter --
352
1056000
3000
17:55
that made her seem like somebody I could have bumped into
353
1059000
2000
17:57
on the streets of New York, or in Vermont, where I'm from.
354
1061000
3000
18:00
But here she had been living in a nunnery for the last seven years.
355
1064000
3000
18:03
I asked her a little bit more about the cave
356
1067000
3000
18:06
and what she planned would happen once she went there, you know.
357
1070000
4000
18:10
What if she saw the truth after just one year,
358
1074000
2000
18:12
what would she do for the next 35 years in her life?
359
1076000
2000
18:14
And this is what she said.
360
1078000
2000
18:16
Woman: I think I'm going to stay for 35. Maybe -- maybe I'll die.
361
1080000
5000
18:21
Jonathan Harris: Maybe you'll die? Woman: Yes.
362
1085000
2000
18:23
JH: 10 years? Woman: Yes, yes. JH: 10 years, that's a long time.
363
1087000
3000
18:26
Woman: Yes, not maybe one, 10 years, maybe I can die
364
1090000
3000
18:29
within one year, or something like that.
365
1093000
2000
18:31
JH: Are you hoping to?
366
1095000
2000
18:33
Woman: Ah, because you know, it's impermanent.
367
1097000
2000
18:35
JH: Yeah, but -- yeah, OK. Do you hope --
368
1099000
6000
18:41
would you prefer to live in the cave for 40 years,
369
1105000
3000
18:44
or to live for one year?
370
1108000
2000
18:46
Woman: But I prefer for maybe 40 to 50.
371
1110000
4000
18:50
JH: 40 to 50? Yeah.
372
1114000
1000
18:51
Woman: Yes. From then, I'm going to the heaven.
373
1115000
3000
18:54
JH: Well, I wish you the best of luck with it.
374
1118000
5000
18:59
Woman: Thank you.
375
1123000
1000
19:00
JH: I hope it's everything that you hope it will be.
376
1124000
3000
19:03
So thank you again, so much.
377
1127000
2000
19:05
Woman: You're most welcome.
378
1129000
2000
19:07
JH: So if you caught that, she said she hoped to die
379
1131000
2000
19:09
when she was around 40. That was enough life for her.
380
1133000
3000
19:12
So, the last thing we did, very quickly,
381
1136000
2000
19:14
is I took all those wish balloons -- there were 117 interviews,
382
1138000
3000
19:17
117 wishes -- and I brought them up to a place called Dochula,
383
1141000
4000
19:21
which is a mountain pass in Bhutan, at 10,300 feet,
384
1145000
4000
19:25
one of the more sacred places in Bhutan.
385
1149000
3000
19:28
And up there, there are thousands of prayer flags
386
1152000
2000
19:30
that people have spread out over the years.
387
1154000
2000
19:32
And we re-inflated all of the balloons, put them up on a string,
388
1156000
3000
19:35
and hung them up there among the prayer flags.
389
1159000
2000
19:37
And they're actually still flying up there today.
390
1161000
2000
19:39
So if any of you have any Bhutan travel plans in the near future,
391
1163000
3000
19:42
you can go check these out. Here are some images from that.
392
1166000
3000
19:46
We said a Buddhist prayer so that all these wishes could come true.
393
1170000
4000
19:59
You can start to see some familiar balloons here.
394
1183000
3000
20:02
"To make some money and to open a store" was the Indian road worker.
395
1186000
5000
20:15
Thanks very much.
396
1199000
2000
20:17
(Applause)
397
1201000
3000

▲Back to top

ABOUT THE SPEAKER
Jonathan Harris - Artist, storyteller, Internet anthropologist
Artist and computer scientist Jonathan Harris makes online art that captures the world's expression -- and gives us a glimpse of the soul of the Internet.

Why you should listen

Brooklyn-based artist Jonathan Harris' work celebrates the world's diversity even as it illustrates the universal concerns of its occupants. His computer programs scour the Internet for unfiltered content, which his beautiful interfaces then organize to create coherence from the chaos.

His projects are both intensely personal (the "We Feel Fine" project, made with Sep Kanvar, which scans the world's blogs to collect snapshots of the writers' feelings) and entirely global (the new "Universe," which turns current events into constellations of words). But their effect is the same -- to show off a world that resonates with shared emotions, concerns, problems, triumphs and troubles.

More profile about the speaker
Jonathan Harris | Speaker | TED.com