How I Teach Kids to Love Science | Cesar Harada | TED Talks

157,903 views ใƒป 2015-11-18

TED


์•„๋ž˜ ์˜๋ฌธ์ž๋ง‰์„ ๋”๋ธ”ํด๋ฆญํ•˜์‹œ๋ฉด ์˜์ƒ์ด ์žฌ์ƒ๋ฉ๋‹ˆ๋‹ค.

๋ฒˆ์—ญ: Ju Hye Lim ๊ฒ€ํ† : Yeram Ha
00:13
When I was a kid, my parents would tell me,
0
13800
2816
์–ด๋ฆฐ์‹œ์ ˆ ๋ถ€๋ชจ๋‹˜์€ ์ œ๊ฒŒ
00:16
"You can make a mess, but you have to clean up after yourself."
1
16640
3399
์–ด์งˆ๋Ÿฌ๋„ ์ข‹์ง€๋งŒ ์Šค์Šค๋กœ ์น˜์šฐ๋ผ๊ณ  ๊ฐ€๋ฅด์น˜์…จ์Šต๋‹ˆ๋‹ค.
00:20
So freedom came with responsibility.
2
20440
3336
์ž์œ ์—๋Š” ์ฑ…์ž„์ด ๋”ฐ๋ž์Šต๋‹ˆ๋‹ค.
00:23
But my imagination would take me to all these wonderful places,
3
23800
3576
ํ•˜์ง€๋งŒ ์ œ ์ƒ์ƒ๋ ฅ์€ ์ €๋ฅผ ํ•ญ์ƒ ๋ฉ‹์ง„ ๊ณณ์œผ๋กœ ๋ฐ๋ ค๋‹ค ์ฃผ์—ˆ๊ณ ,
00:27
where everything was possible.
4
27400
2096
๊ทธ ๊ณณ์—์„œ๋Š” ๋ชจ๋“  ๊ฒŒ ๊ฐ€๋Šฅํ–ˆ์Šต๋‹ˆ๋‹ค.
00:29
So I grew up in a bubble of innocence --
5
29520
2896
๊ทธ๋ž˜์„œ ์ €๋Š” ์ˆœ์ˆ˜ํ•จ ์†์— ์ž๋ž์Šต๋‹ˆ๋‹ค.
00:32
or a bubble of ignorance, I should say,
6
32440
2336
์–ด๋–ป๊ฒŒ ๋ณด๋ฉด ๋ฌด์ง€ํ•˜๊ฒŒ ์ž๋ž€ ๊ฒƒ ๊ฐ™์Šต๋‹ˆ๋‹ค.
00:34
because adults would lie to us to protect us from the ugly truth.
7
34800
5096
์–ด๋ฅธ๋“ค์€ ์šฐ๋ฆฌ๋ฅผ ์ถ”ํ•œ ์ง„์‹ค๋กœ๋ถ€ํ„ฐ ๋ณดํ˜ธํ•˜๊ธฐ ์œ„ํ•ด ๊ฑฐ์ง“๋ง์„ ํ•˜๋‹ˆ๊นŒ์š”.
00:39
And growing up, I found out that adults make a mess,
8
39920
3576
์ €๋Š” ์ž๋ผ๋ฉด์„œ ์–ด๋ฅธ๋“ค๋„ ์–ด์ง€๋ฅด์ง€๋งŒ
00:43
and they're not very good at cleaning up after themselves.
9
43520
2800
์Šค์Šค๋กœ ์น˜์šฐ๋Š” ๊ฒƒ์€ ์ž˜ํ•˜์ง€ ๋ชปํ•œ๋‹ค๋Š” ๊ฒƒ์„ ์•Œ๊ฒŒ ๋˜์—ˆ์Šต๋‹ˆ๋‹ค.
00:47
Fast forward, I am an adult now,
10
47360
2136
์–ด๋Š์ƒˆ ์ €๋Š” ์–ด๋ฅธ์ด ๋˜์—ˆ์Šต๋‹ˆ๋‹ค.
00:49
and I teach citizen science and invention at the Hong Kong Harbour School.
11
49520
4976
์ €๋Š” ํ™์ฝฉํ•˜๋ฒ„ํ•™๊ต์—์„œ ์‹œ๋ฏผ ์ฐธ์—ฌํ˜• ๊ณผํ•™๊ณผ ๋ฐœ๋ช…์— ๋Œ€ํ•ด ๊ฐ€๋ฅด์น˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
00:54
And it doesn't take too long
12
54520
1336
์ œ ํ•™์ƒ๋“ค์ด ํ•ด๋ณ€๊ฐ€๋ฅผ ๊ฑท๋‹ค๊ฐ€
00:55
before my students walk on a beach and stumble upon piles of trash.
13
55880
4216
์–ผ๋งˆ ๊ฐ€์ง€ ์•Š์•„ ์“ฐ๋ ˆ๊ธฐ ๋”๋ฏธ์™€ ๋งˆ์ฃผ์น˜๋Š” ์ผ์€ ์ž์ฃผ ์žˆ์Šต๋‹ˆ๋‹ค.
01:00
So as good citizens, we clean up the beaches --
14
60120
2656
๊ทธ๋ž˜์„œ ์ฐฉํ•œ ์‹œ๋ฏผ์œผ๋กœ์„œ ์šฐ๋ฆฌ๋Š” ํ•ด๋ณ€๊ฐ€์˜ ์“ฐ๋ ˆ๊ธฐ๋ฅผ ์น˜์›๋‹ˆ๋‹ค
01:02
and no, he is not drinking alcohol, and if he is, I did not give it to him.
15
62800
4720
์ € ์•„์ด๋Š” ์ˆ ์„ ๋งˆ์‹œ๋Š” ๊ฒŒ ์•„๋‹™๋‹ˆ๋‹ค. ๋งŒ์•ฝ ๋งˆ์‹ ๋‹ค๋ฉด ์ œ๊ฐ€ ์ค€ ๊ฒŒ ์•„๋‹™๋‹ˆ๋‹ค.
01:07
(Laughter)
16
67880
1760
(์›ƒ์Œ)
01:09
And so it's sad to say,
17
69960
1216
์ด๋Ÿฐ ๋ง์„ ํ•˜๋Š” ๊ฒƒ์ด ์ฐธ ์Šฌํ”„์ง€๋งŒ
01:11
but today more than 80 percent of the oceans have plastic in them.
18
71200
3776
์˜ค๋Š˜๋‚  80% ์ด์ƒ์˜ ๋ฐ”๋‹ค์— ํ”Œ๋ผ์Šคํ‹ฑ์ด ์žˆ์Šต๋‹ˆ๋‹ค.
01:15
It's a horrifying fact.
19
75000
1280
๋”์ฐํ•œ ์‚ฌ์‹ค์ด์ฃ .
01:16
And in past decades,
20
76800
1376
์ง€๋‚œ ๋ช‡ ์‹ญ ๋…„ ๋™์•ˆ,
01:18
we've been taking those big ships out and those big nets,
21
78200
3456
์šฐ๋ฆฌ๋Š” ํฐ ๊ทธ๋ฌผ์„ ์‹ค์€ ํฐ ๋ฐฐ๋ฅผ ํƒ€๊ณ  ๋‚˜๊ฐ€์„œ,
01:21
and we collect those plastic bits that we look at under a microscope,
22
81680
3336
์ด๋Ÿฐ ํ”Œ๋ผ์Šคํ‹ฑ ์กฐ๊ฐ๋“ค์„ ๋ชจ์•„ ํ˜„๋ฏธ๊ฒฝ์œผ๋กœ ๋“ค์—ฌ๋‹ค๋ณด๊ณ ,
01:25
and we sort them,
23
85040
1216
๊ทธ๊ฒƒ๋“ค์„ ๋ถ„๋ฅ˜ํ•˜๊ณ ,
01:26
and then we put this data onto a map.
24
86280
1762
์ด๋Ÿฐ ๋ฐ์ดํ„ฐ๋ฅผ ์ง€๋„์— ์˜ฎ๊ฒจ์ ์–ด ์™”์Šต๋‹ˆ๋‹ค.
01:28
But that takes forever, it's very expensive,
25
88440
2336
์ด ๊ณผ์ •์€ ์—„์ฒญ๋‚œ ์‹œ๊ฐ„๊ณผ ๋ˆ์ด ๋“ญ๋‹ˆ๋‹ค.
01:30
and so it's quite risky to take those big boats out.
26
90800
3136
๊ทธ๋ž˜์„œ ํฐ ๋ฐฐ๋“ค์„ ๋Œ๊ณ  ๋‚˜๊ฐ€๋Š” ๊ฒƒ์€ ์œ„ํ—˜๋ถ€๋‹ด์ด ํฐ ์ผ์ž…๋‹ˆ๋‹ค.
01:33
So with my students, ages six to 15,
27
93960
2936
๊ทธ๋ž˜์„œ ์ €๋Š” 6์‚ด๋ถ€ํ„ฐ 15์‚ด๊นŒ์ง€์˜ ์ œ ํ•™์ƒ๋“ค๊ณผ ํ•จ๊ป˜,
01:36
we've been dreaming of inventing a better way.
28
96920
2216
๋” ๋‚˜์€ ๋ฐฉ๋ฒ•์„ ๋ฐœ๋ช…ํ•˜๋Š” ๊ฒƒ์„ ํ•ญ์ƒ ๊ฟˆ๊ฟ”์™”์Šต๋‹ˆ๋‹ค.
01:39
So we've transformed our tiny Hong Kong classroom into a workshop.
29
99160
4416
๊ทธ๋ž˜์„œ ํ•™๊ต์˜ ์ž‘์€ ๊ต์‹ค์„ ์ž‘์—…์žฅ์œผ๋กœ ๋ฐ”๊ฟจ์Šต๋‹ˆ๋‹ค.
01:43
And so we started building this small workbench,
30
103600
2656
๊ทธ๋ฆฌ๊ณ  ์ž‘์€ ์ž‘์—…๋Œ€๋ฅผ ๋งŒ๋“ค๊ธฐ ์‹œ์ž‘ํ–ˆ์Šต๋‹ˆ๋‹ค.
01:46
with different heights, so even really short kids can participate.
31
106280
3176
๋†’์ด๋ฅผ ๋‹ค๋ฅด๊ฒŒ ํ•ด์„œ ํ‚ค๊ฐ€ ์ž‘์€ ์•„์ด๋„ ์ฐธ์—ฌํ•  ์ˆ˜ ์žˆ๊ฒŒ ํ–ˆ์Šต๋‹ˆ๋‹ค.
01:49
And let me tell you, kids with power tools are awesome and safe.
32
109480
4176
์•„์ด๋“ค์ด ์ „๋™๊ณต๊ตฌ๋ฅผ ๋งŒ์ง€๋Š” ๊ฒƒ์€ ๋ฉ‹์ง€๊ณ  ์•ˆ์ „ํ•œ ์ผ์ž…๋‹ˆ๋‹ค.
01:53
(Laughter)
33
113680
1336
(์›ƒ์Œ)
01:55
Not really.
34
115040
1896
๊ทธ๋ ‡์ง€ ์•Š์Šต๋‹ˆ๋‹ค.
01:56
And so, back to plastic.
35
116960
1216
ํ”Œ๋ผ์Šคํ‹ฑ ์ด์•ผ๊ธฐ๋กœ ๋Œ์•„๊ฐ‘์‹œ๋‹ค.
01:58
We collect this plastic and we grind it to the size we find it in the ocean,
36
118200
3616
์šฐ๋ฆฌ๋Š” ํ”Œ๋ผ์Šคํ‹ฑ์„ ๋ชจ์•„์„œ ๋ฐ”๋‹ค์—์„œ ์•Œ์•„๋ณผ ์ˆ˜ ์žˆ๋Š” ํฌ๊ธฐ๋กœ ๋ถ€์ˆฉ๋‹ˆ๋‹ค.
02:01
which is very small because it breaks down.
37
121840
2176
๋‚˜์ค‘์— ๋ถ„ํ•ด๋˜๊ธฐ ๋•Œ๋ฌธ์— ๋งค์šฐ ์ž‘์ฃ .
02:04
And so this is how we work.
38
124040
1376
์ด๊ฒŒ ์ €ํฌ๊ฐ€ ์ผํ•˜๋Š” ๋ฐฉ์‹์ž…๋‹ˆ๋‹ค.
02:05
I let the imaginations of my students run wild.
39
125440
3136
์ €๋Š” ํ•™์ƒ๋“ค์ด ๋งˆ์Œ๊ป ์ƒ์ƒ์˜ ๋‚˜๋ž˜๋ฅผ ํŽผ์น  ์ˆ˜ ์žˆ๊ฒŒ ๋†”๋‘ก๋‹ˆ๋‹ค.
02:08
And my job is to try to collect the best of each kid's idea
40
128600
4256
์ œ ์—ญํ• ์€ ์•„์ด๋“ค์˜ ์•„์ด๋””์–ด ์ค‘์— ์ตœ๊ณ ์˜ ๊ฒƒ์„ ๋ชจ์œผ๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.
02:12
and try to combine it into something that hopefully would work.
41
132880
4280
๊ทธ๋ฆฌ๊ณ  ์ด ์•„์ด๋””์–ด๋ฅผ ํฌ๋ง์ ์œผ๋กœ ์ˆ˜ํ–‰๋˜๋„๋ก ์กฐํ•ฉํ•ฉ๋‹ˆ๋‹ค.
02:17
And so we have agreed that instead of collecting plastic bits,
42
137920
3136
๊ทธ๋ž˜์„œ ์šฐ๋ฆฌ๋Š” ํ”Œ๋ผ์Šคํ‹ฑ ์กฐ๊ฐ์„ ๋ชจ์œผ๋Š” ๋Œ€์‹ ,
02:21
we are going to collect only the data.
43
141080
1976
๋ฐ์ดํ„ฐ๋งŒ์„ ๋ชจ์œผ๊ธฐ๋กœ ํ–ˆ์Šต๋‹ˆ๋‹ค.
02:23
So we're going to get an image of the plastic with a robot --
44
143080
2976
์šฐ๋ฆฌ๋Š” ๋กœ๋ด‡์œผ๋กœ ํ”Œ๋ผ์Šคํ‹ฑ์˜ ์ด๋ฏธ์ง€๋ฅผ ๋ฐ›์„ ๊ฒƒ์ž…๋‹ˆ๋‹ค.
02:26
so robots, kids get very excited.
45
146080
2376
์•„์ด๋“ค์€ ๋กœ๋ด‡์— ๊ธฐ๋ปํ•˜์ฃ .
02:28
And the next thing we do -- we do what we call "rapid prototyping."
46
148480
3143
๊ทธ ๋‹ค์Œ์—๋Š” "์พŒ์†์‹œ์ž‘๊ธฐ์ˆ "์ด๋ผ๊ณ  ๋ถˆ๋ฆฌ๋Š” ๊ฒƒ์„ ํ•˜๊ฒŒ ๋˜๋Š”๋ฐ,
02:31
We are so rapid at prototyping
47
151647
1689
๊ต‰์žฅํžˆ ๋นจ๋ฆฌ ํ•ด์„œ
02:33
that the lunch is still in the lunchbox when we're hacking it.
48
153360
3176
์ ์‹ฌ์„ ๋‹ค ๋จน๊ธฐ๋„ ์ „์— ๋ถ„ํ•ด๊นŒ์ง€ ๋๋ƒ…๋‹ˆ๋‹ค.
02:36
(Laughter)
49
156560
1296
(์›ƒ์Œ)
02:37
And we hack table lamps and webcams, into plumbing fixtures
50
157880
4256
์šฐ๋ฆฌ๋Š” ์Šคํƒ ๋“œ๋ž‘ ์›น์บ ๋„ ๋ถ„ํ•ดํ•ด์„œ ๋ฐฐ๊ด€๊ธฐ๊ตฌ์— ๋„ฃ๊ณ ,
02:42
and we assemble that into a floating robot that will be slowly moving through water
51
162160
5136
์ด๊ฒƒ๋“ค์„ ์กฐ๋ฆฝํ•˜์—ฌ ํ”Œ๋ผ์Šคํ‹ฑ ์กฐ๊ฐ ์‚ฌ์ด์—์„œ
02:47
and through the plastic that we have there --
52
167320
2096
๋ฌผ ์œ„๋ฅผ ์ฒœ์ฒœํžˆ ๋– ๋‹ค๋‹ˆ๋Š” ๋กœ๋ด‡์„ ๋งŒ๋“ค๊ฒŒ ๋ฉ๋‹ˆ๋‹ค.
02:49
and this is the image that we get in the robot.
53
169440
2191
์ด๊ฒŒ ๋กœ๋ด‡์œผ๋กœ๋ถ€ํ„ฐ ์ˆ˜์‹ ๋œ ์ด๋ฏธ์ง€์ž…๋‹ˆ๋‹ค.
02:51
So we see the plastic pieces floating slowly through the sensor,
54
171655
3721
์šฐ๋ฆฌ๋Š” ํ”Œ๋ผ์Šคํ‹ฑ ์กฐ๊ฐ๋“ค์ด ์„ผ์„œ๋ฅผ ์ง€๋‚˜๊ฐ€๋Š” ๊ฒƒ์„ ๋ณผ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
02:55
and the computer on board will process this image,
55
175400
3296
๋กœ๋ด‡ ์•ˆ์˜ ์ปดํ“จํ„ฐ๊ฐ€ ์ด๋Ÿฐ ์ด๋ฏธ์ง€๋ฅผ ์ฒ˜๋ฆฌํ•˜์—ฌ,
02:58
and measure the size of each particle,
56
178720
2096
์กฐ๊ฐ๋“ค์˜ ํฌ๊ธฐ๋ฅผ ์ธก์ •ํ•ด์„œ,
03:00
so we have a rough estimate of how much plastic there is in the water.
57
180840
4120
์šฐ๋ฆฌ๋Š” ๋ฌผ ์†์— ์–ผ๋งŒํผ์˜ ํ”Œ๋ผ์Šคํ‹ฑ์ด ์žˆ๋Š”์ง€ ๋Œ€๋žต์ ์œผ๋กœ ๊ณ„์‚ฐํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
03:05
So we documented this invention step by step
58
185520
3016
์šฐ๋ฆฌ๋Š” ๋ฐœ๋ช…๊ฐ€๋“ค์„ ์œ„ํ•œ ์›น์‚ฌ์ดํŠธ์ธ ์ธ์ŠคํŠธ๋Ÿญํ„ฐ๋ธ”์Šค์—
03:08
on a website for inventors called Instructables,
59
188560
3376
์ด ๋ฐœ๋ช…์„ ๋‹จ๊ณ„๋ณ„๋กœ ๊ธฐ๋กํ–ˆ์Šต๋‹ˆ๋‹ค.
03:11
in the hope that somebody would make it even better.
60
191960
2800
๋ˆ„๊ตฐ๊ฐ€ ๋” ์ข‹๊ฒŒ ๊ฐœ์„ ํ•ด ์ฃผ๊ธฐ๋ฅผ ๋ฐ”๋ผ๋Š” ๋งˆ์Œ์—์š”.
03:15
What was really cool about this project was that the students saw a local problem,
61
195838
3858
์ด ํ”„๋กœ์ ํŠธ๊ฐ€ ์ •๋ง ๋ฉ‹์กŒ๋˜ ์ด์œ ๋Š” ํ•™์ƒ๋“ค์ด ์ง€์—ญ์‚ฌํšŒ์˜ ๋ฌธ์ œ์ ์„ ๋ณด๊ณ ,
03:19
and boom -- they are trying to immediately address it.
62
199720
2667
์ฆ‰์‹œ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๋ ค๊ณ  ํ–ˆ๋‹ค๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.
03:22
[I can investigate my local problem]
63
202411
2325
[์ €๋Š” ์ง€์—ญ์‚ฌํšŒ์˜ ๋ฌธ์ œ๋ฅผ ์กฐ์‚ฌํ•  ์ˆ˜ ์žˆ์–ด์š”.]
03:24
But my students in Hong Kong are hyperconnected kids.
64
204760
3216
ํ•˜์ง€๋งŒ ์ œ ํ•™์ƒ๋“ค์€ ์™ธ๋ถ€์™€ ๊ณผ๋„ํ•˜๊ฒŒ ์—ฐ๊ฒฐ๋œ ์•„์ด๋“ค์ž…๋‹ˆ๋‹ค.
03:28
And they watch the news, they watch the Internet,
65
208000
2296
๋‰ด์Šค๋„ ๋ณด๊ณ  ์ธํ„ฐ๋„ท๋„ ํ•˜์ฃ .
03:30
and they came across this image.
66
210320
2240
๊ทธ๋Ÿฌ๋‹ค๊ฐ€ ์•„์ด๋“ค์€ ์ด๋Ÿฐ ์ด๋ฏธ์ง€๋ฅผ ๋ณด๊ฒŒ ๋˜์—ˆ์Šต๋‹ˆ๋‹ค.
03:33
This was a child, probably under 10, cleaning up an oil spill bare-handed,
67
213840
4736
10์‚ด๋„ ์•ˆ ๋˜์–ด๋ณด์ด๋Š” ์•„์ด๊ฐ€ ๋งจ์†์œผ๋กœ ์œ ์ถœ๋œ ๊ธฐ๋ฆ„์„ ์น˜์šฐ๊ณ  ์žˆ์—ˆ์Šต๋‹ˆ๋‹ค.
03:38
in the Sundarbans, which is the world's largest mangrove forest in Bangladesh.
68
218600
4496
์„ธ๊ณ„์—์„œ ๊ฐ€์žฅ ํฐ ๋งน๊ทธ๋กœ๋ธŒ ์ˆฒ์ด ์žˆ๋Š” ๋ฐฉ๊ธ€๋ผ๋ฐ์‹œ ์ˆœ๋‹ค๋ฅด๋ฐ˜์Šค ์ง€์—ญ์ž…๋‹ˆ๋‹ค.
03:43
So they were very shocked,
69
223120
2456
์•„์ด๋“ค์€ ์ถฉ๊ฒฉ์„ ๋งŽ์ด ๋ฐ›์•˜์Šต๋‹ˆ๋‹ค.
03:45
because this is the water they drink, this is the water they bathe in,
70
225600
3296
์ด ๋ฌผ์ด ๋ฐ”๋กœ ๊ทธ๋“ค์ด ๋งˆ์‹œ๊ณ  ์”ป๊ณ ,
03:48
this is the water they fish in -- this is the place where they live.
71
228920
3376
๊ณ ๊ธฐ๋ฅผ ์žก๊ณ , ๊ทธ๋“ค์ด ์‚ฌ๋Š” ํ„ฐ์ „์ด๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค.
03:52
And also you can see the water is brown, the mud is brown and oil is brown,
72
232320
3896
๋ฌผ์ด ๊ฐˆ์ƒ‰์ธ ๊ฒƒ์„ ๋ณด์‹ค ์ˆ˜ ์žˆ๋Š”๋ฐ, ์ง„ํ™๊ณผ ๊ธฐ๋ฆ„์ด ๊ฐˆ์ƒ‰์ž…๋‹ˆ๋‹ค.
03:56
so when everything is mixed up,
73
236240
1477
๋ชจ๋“  ๊ฒŒ ๋’ค์„ž์—ฌ์žˆ์Šต๋‹ˆ๋‹ค.
03:57
it's really hard to see what's in the water.
74
237741
2475
๋ฌผ์— ๋ญ๊ฐ€ ์žˆ๋Š”์ง€๋„ ๋ณด๊ธฐ ์–ด๋ ต์Šต๋‹ˆ๋‹ค.
04:00
But, there's a technology that's rather simple,
75
240240
2256
๊ทธ๋ ‡์ง€๋งŒ ๋ฌผ ์†์— ๋ฌด์—‡์ด ์žˆ๋Š”์ง€ ๋ณด์—ฌ์ฃผ๋Š”
04:02
that's called spectrometry,
76
242520
1536
๋ถ„๊ด‘๋ถ„์„์ด๋ผ๋Š”
04:04
that allows you see what's in the water.
77
244080
1905
๊ต‰์žฅํžˆ ๊ฐ„๋‹จํ•œ ๊ธฐ์ˆ ์ด ์žˆ์Šต๋‹ˆ๋‹ค.
04:06
So we built a rough prototype of a spectrometer,
78
246009
3047
๊ทธ๋ž˜์„œ ์šฐ๋ฆฌ๋Š” ๋ถ„๊ด‘๊ณ„ ์‹œํ—˜๋ชจํ˜•์„ ๋งŒ๋“ค์—ˆ์Šต๋‹ˆ๋‹ค.
04:09
and you can shine light through different substances
79
249080
2936
๋‹ค์–‘ํ•œ ๋ฌผ์งˆ๋“ค ์‚ฌ์ด๋กœ ๋น›์„ ๋น„์ถœ ์ˆ˜ ์žˆ๋Š”๋ฐ,
04:12
that produce different spectrums,
80
252040
2416
๋‹ค๋ฅธ ์ŠคํŽ™ํŠธ๋Ÿผ์„ ๋งŒ๋“ค์–ด๋ƒ…๋‹ˆ๋‹ค.
04:14
so that can help you identify what's in the water.
81
254480
3856
์ด๊ฑธ๋กœ ๋ฌผ ์†์— ๋ฌด์—‡์ด ์žˆ๋Š”์ง€ ์•Œ์•„๋‚ผ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
04:18
So we packed this prototype of a sensor,
82
258360
2896
๊ทธ๋ž˜์„œ ์šฐ๋ฆฌ๋Š” ์‹œํ—˜๋ชจํ˜• ์„ผ์„œ๋ฅผ ํฌ์žฅํ•ด์„œ,
04:21
and we shipped it to Bangladesh.
83
261280
2240
๋ฐฉ๊ธ€๋ผ๋ฐ์‹œ๋กœ ๋ณด๋ƒˆ์Šต๋‹ˆ๋‹ค.
04:23
So what was cool about this project
84
263989
1667
์ด ํ”„๋กœ์ ํŠธ๊ฐ€ ๋ฉ‹์žˆ์—ˆ๋˜ ์ ์€,
04:25
was that beyond addressing a local problem,
85
265680
3135
์ œ ํ•™์ƒ๋“ค์ด ์ง€์—ญ์‚ฌํšŒ ๋ฌธ์ œ๋งŒ ๋ฐ”๋ผ๋ณด๊ณ 
04:28
or looking at a local problem,
86
268839
1430
ํ•ด๊ฒฐํ•˜๋Š” ๊ฒƒ์„ ๋„˜์–ด์„œ,
04:30
my students used their empathy and their sense of being creative
87
270293
3923
๊ณต๊ฐ๋Šฅ๋ ฅ๊ณผ ์ฐฝ์˜๋ ฅ์„ ์ด์šฉํ•ด์„œ
04:34
to help, remotely, other kids.
88
274240
2256
๋จผ ๊ณณ์˜ ๋‹ค๋ฅธ ์•„์ด๋“ค์—๊ฒŒ ๋„์›€์„ ์ฃผ์—ˆ๋‹ค๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.
04:36
[I can investigate a remote problem]
89
276520
1715
[์ €๋Š” ๋‹ค๋ฅธ ์ง€์—ญ์˜ ๋ฌธ์ œ๋„ ํ•ด๊ฒฐํ•  ์ˆ˜ ์žˆ์–ด์š”.]
04:38
So I was very compelled by doing the second experiments,
90
278259
2620
์ €๋Š” ๋‘ ๋ฒˆ์งธ ์‹คํ—˜ ์ดํ›„์—
04:40
and I wanted to take it even further --
91
280903
2513
์ด๊ฑธ ์ข€ ๋” ๋ฉ€๋ฆฌ ๋Œ๊ณ  ๋‚˜๊ฐ€๊ณ  ์‹ถ์–ด์กŒ์Šต๋‹ˆ๋‹ค.
04:43
maybe addressing an even harder problem, and it's also closer to my heart.
92
283440
4600
๋” ์–ด๋ ค์šด ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•ด๋ณธ๋‹ค๋˜๊ฐ€์š”, ์‚ฌ์‹ค ์ œ ๋งˆ์Œ์ด ๋” ๊ฐ€๋Š” ๋ฌธ์ œ๋“ค์ž…๋‹ˆ๋‹ค.
04:48
So I'm half Japanese and half French,
93
288560
2616
์ €๋Š” ์ผ๋ณธ๊ณผ ํ”„๋ž‘์Šค ํ˜ผํ˜ˆ์ธ์ž…๋‹ˆ๋‹ค.
04:51
and maybe you remember in 2011 there was a massive earthquake in Japan.
94
291200
5320
2011๋…„์— ์ผ๋ณธ์—์„œ ์ผ์–ด๋‚ฌ๋˜ ๋Œ€์ง€์ง„์„ ๊ธฐ์–ตํ•˜์‹ค๊ฒ๋‹ˆ๋‹ค.
04:57
It was so violent that it triggered several giant waves --
95
297120
3816
๋„ˆ๋ฌด ๊ฐ•๋ ฅํ•ด์„œ ์“ฐ๋‚˜๋ฏธ๋ผ๊ณ  ๋ถˆ๋ฆฌ๋Š”
05:00
they are called tsunami --
96
300960
1416
๊ฑฐ๋Œ€ํ•œ ํŒŒ๋„๋ฅผ ๋งŒ๋“ค์–ด๋ƒˆ๋Š”๋ฐ,
05:02
and those tsunami destroyed many cities on the eastern coast of Japan.
97
302400
6960
์“ฐ๋‚˜๋ฏธ๋Š” ์ผ๋ณธ ๋™ํ•ด์•ˆ์˜ ๋งŽ์€ ๋„์‹œ๋“ค์„ ํŒŒ๊ดดํ–ˆ์Šต๋‹ˆ๋‹ค.
05:10
More than 14,000 people died in an instant.
98
310680
3360
์ˆœ์‹๊ฐ„์— 14000๋ช…์ด ๋„˜๋Š” ์‚ฌ๋žŒ๋“ค์ด ์ฃฝ์—ˆ์Šต๋‹ˆ๋‹ค.
05:15
Also, it damaged the nuclear power plant of Fukushima,
99
315600
3736
ํ›„์ฟ ์‹œ๋งˆ์— ์žˆ๋˜ ์›์ „๋„ ํ”ผํ•ด๋ฅผ ์ž…์—ˆ๋Š”๋ฐ
05:19
the nuclear power plant just by the water.
100
319360
2680
๋ฐ”๋‹ค ๋ฐ”๋กœ ์˜†์— ์žˆ๋Š” ์›์ „์ด์—ˆ์Šต๋‹ˆ๋‹ค.
05:22
And today, I read the reports
101
322480
2416
๊ทธ๋ฆฌ๊ณ  ์˜ค๋Š˜ ์‹ ๋ฌธ์„ ๋ณด๋‹ˆ,
05:24
and an average of 300 tons
102
324920
3056
ํ‰๊ท  300ํ†ค์ด
05:28
are leaking from the nuclear power plant into the Pacific Ocean.
103
328000
3576
์›์ „์—์„œ ํƒœํ‰์–‘์œผ๋กœ ํ˜๋Ÿฌ ๋‚˜๊ฐ„๋‹ค๊ณ  ํ•ฉ๋‹ˆ๋‹ค.
05:31
And today the whole Pacific Ocean has traces of contamination of cesium-137.
104
331600
6376
์˜ค๋Š˜ ํƒœํ‰์–‘ ์ „์—ญ์ด ์„ธ์Š˜-137์— ์˜ค์—ผ๋œ ํ”์ ์„ ๋ณด์ด๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
05:38
If you go outside on the West Coast, you can measure Fukushima everywhere.
105
338000
4416
์„œํ•ด์•ˆ์œผ๋กœ ๋‚˜๊ฐ€๋ฉด ํ›„์ฟ ์‹œ๋งˆ์˜ ์˜ํ–ฅ์„ ์–ด๋””์„œ๋“  ์ธก์ •ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
05:42
But if you look at the map, it can look like most of the radioactivity
106
342440
3296
ํ•˜์ง€๋งŒ ์ง€๋„๋ฅผ ๋ณด๋ฉด ๋ฐฉ์‚ฌ๋Šฅ์˜ ๋Œ€๋ถ€๋ถ„์ด
05:45
has been washed away from the Japanese coast,
107
345760
2096
์ผ๋ณธ์˜ ํ•ด์•ˆ์—์„œ ์”ป๊ฒจ๋‚˜๊ฐ„ ๊ฒƒ์ฒ˜๋Ÿผ ๋ณด์ผ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
05:47
and most of it is now -- it looks like it's safe, it's blue.
108
347880
2816
์ด์ œ ๋Œ€๋ถ€๋ถ„์ด ํŒŒ๋ž€์ƒ‰์œผ๋กœ ์•ˆ์ „ํ•œ ๊ฒƒ์ฒ˜๋Ÿผ ๋ณด์ž…๋‹ˆ๋‹ค.
05:50
Well, reality is a bit more complicated than this.
109
350720
3416
ํ•˜์ง€๋งŒ ํ˜„์‹ค์€ ์ด๋ณด๋‹ค ๋ณต์žกํ•ฉ๋‹ˆ๋‹ค.
05:54
So I've been going to Fukushima every year since the accident,
110
354160
3656
์ €๋Š” ์‚ฌ๊ณ  ์ดํ›„ ๋งค๋…„ ํ›„์ฟ ์‹œ๋งˆ๋ฅผ ๋ฐฉ๋ฌธํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
05:57
and I measure independently and with other scientists,
111
357840
2536
ํ˜ผ์ž์„œ, ๋˜๋Š” ๋‹ค๋ฅธ ๊ณผํ•™์ž๋“ค๊ณผ ํ•จ๊ป˜
06:00
on land, in the river --
112
360400
1856
์œก์ง€์™€ ๊ฐ•์„ ์กฐ์‚ฌํ•ฉ๋‹ˆ๋‹ค.
06:02
and this time we wanted to take the kids.
113
362280
2736
์ด๋ฒˆ์—๋Š” ์ €๋Š” ์•„์ด๋“ค์„ ๋ฐ๋ ค๊ฐ€๊ณ  ์‹ถ์—ˆ์Šต๋‹ˆ๋‹ค.
06:05
So of course we didn't take the kids, the parents wouldn't allow that to happen.
114
365040
3776
๋ฌผ๋ก  ๋ฐ๋ ค๊ฐ€์ง€ ์•Š์•˜์Šต๋‹ˆ๋‹ค. ํ•™๋ถ€๋ชจ๋“ค์ด ๋ฐ˜๋Œ€ํ•  ํ…Œ๋‹ˆ๊นŒ์š”.
06:08
(Laughter)
115
368840
1336
(์›ƒ์Œ)
06:10
But every night we would report to "Mission Control" --
116
370200
3936
ํ•˜์ง€๋งŒ ๋งค์ผ ๋ฐค ์šฐ๋ฆฌ๋Š” "๊ด€์ œ์„ผํ„ฐ"์— ๋ณด๊ณ ํ•ฉ๋‹ˆ๋‹ค.
06:14
different masks they're wearing.
117
374160
2176
๋‹ค ๋‹ค๋ฅธ ๊ฐ€๋ฉด์„ ์“ฐ๊ณ ์žˆ์ฃ .
06:16
It could look like they didn't take the work seriously, but they really did
118
376360
4376
์ผ์„ ์ง„์ง€ํ•˜๊ฒŒ ์ƒ๊ฐํ•˜์ง€ ์•Š๋Š” ๊ฒƒ์ฒ˜๋Ÿผ ๋ณด์ผ ์ˆ˜๋„ ์žˆ๊ฒ ์ง€๋งŒ ๊ทธ๋ ‡์ง€ ์•Š์Šต๋‹ˆ๋‹ค.
06:20
because they're going to have to live with radioactivity their whole life.
119
380760
4200
๋‚จ์€ ์ธ์ƒ์„ ๋ฐฉ์‚ฌ๋Šฅ ์†์— ์‚ด์•„๊ฐ€์•ผ ํ•˜๋‹ˆ๊นŒ์š”.
06:25
And so what we did with them
120
385640
2056
๊ทธ๋ž˜์„œ ์šฐ๋ฆฌ๋Š” ๊ทธ๋“ค๊ณผ
06:27
is that we'd discuss the data we collected that day,
121
387720
2616
๊ทธ ๋‚  ๋ชจ์€ ์ž๋ฃŒ๋กœ ํ† ๋ก ํ–ˆ์Šต๋‹ˆ๋‹ค.
06:30
and talk about where we should be going next --
122
390360
2191
๋‹ค์Œ์—๋Š” ์–ด๋”” ๊ฐˆ์ง€ ์ „๋žต, ์ผ์ • ๋“ฑ์— ๋Œ€ํ•ด
06:32
strategy, itinerary, etc...
123
392575
2121
์ด์•ผ๊ธฐํ–ˆ์Šต๋‹ˆ๋‹ค.
06:34
And to do this, we built a very rough topographical map
124
394720
3616
๊ทธ๋Ÿฌ๊ธฐ ์œ„ํ•ด์„œ ์šฐ๋ฆฌ๋Š” ์›์ „ ์ฃผ์œ„์˜
06:38
of the region around the nuclear power plant.
125
398360
2856
์ง€์—ญ์— ๋Œ€ํ•œ ๋Œ€๋žต์ ์ธ ์ง€ํ˜•๋„๋ฅผ ๋งŒ๋“ค์—ˆ์Šต๋‹ˆ๋‹ค.
06:41
And so we built the elevation map,
126
401240
2016
์ž…๋ฉด์ง€๋„๋„ ๋งŒ๋“ค์–ด์„œ,
06:43
we sprinkled pigments to represent real-time data for radioactivity,
127
403280
4616
๋ฐฉ์‚ฌ๋Šฅ์˜ ์‹ค์‹œ๊ฐ„ ์ž๋ฃŒ๋ฅผ ๋ณด์—ฌ์ฃผ๊ธฐ ์œ„ํ•ด ์ƒ‰์†Œ๋ฅผ ๋ฟŒ๋ฆฌ๊ณ 
06:47
and we sprayed water to simulate the rainfall.
128
407920
4336
ํญํฌ์‹œ์—ฐ์„ ์œ„ํ•ด ๋ฌผ๋„ ๋ฟŒ๋ ธ์Šต๋‹ˆ๋‹ค.
06:52
And with this we could see that the radioactive dust
129
412280
2976
์ด ์ง€๋„๋“ค๋กœ ์šฐ๋ฆฌ๋Š” ๋ฐฉ์‚ฌ์„ฑ ๋จผ์ง€๊ฐ€
06:55
was washing from the top of the mountain into the river system,
130
415280
3056
์‚ฐ ๊ผญ๋Œ€๊ธฐ์—์„œ ๊ฐ•์œผ๋กœ ์”ป๊ฒจ๋‚ด๋ ค๊ฐ€
06:58
and leaking into the ocean.
131
418360
1536
๋ฐ”๋‹ค๋กœ ํ˜๋Ÿฌ๋“ค์–ด๊ฐ€๋Š” ๊ฒƒ์„ ๋ณผ ์ˆ˜ ์žˆ์—ˆ์Šต๋‹ˆ๋‹ค.
06:59
So it was a rough estimate.
132
419920
1600
์ด๊ฒƒ์€ ๋Œ€๋žต์ ์ธ ์ถ”์ธก์ด์—ˆ์Šต๋‹ˆ๋‹ค.
07:02
But with this in mind, we organized this expedition,
133
422680
2936
ํ•˜์ง€๋งŒ ์ด๊ฒƒ์„ ์—ผ๋‘์— ๋‘๊ณ  ์šฐ๋ฆฌ๋Š”,
07:05
which was the closest civilians have been to the nuclear power plant.
134
425640
3616
๋ฏผ๊ฐ„์ธ์œผ๋กœ์„œ ์›์ „์— ๊ฐ€์žฅ ๊ฐ€๊นŒ์ด ๊ฐ€๋Š” ํƒ์‚ฌ๋ฅผ ๊ณ„ํšํ–ˆ์Šต๋‹ˆ๋‹ค.
07:09
We are sailing 1.5 kilometers away from the nuclear power plant,
135
429280
4336
์›์ „์—์„œ 1.5km ๋–จ์–ด์ง„ ๊ณณ์— ๊ฐ€์„œ
07:13
and with the help of the local fisherman,
136
433640
1953
๊ทธ ์ง€์—ญ ์–ด๋ถ€๋“ค์˜ ๋„์›€์„ ๋ฐ›์•„
07:15
we are collecting sediment from the seabed
137
435617
2239
์šฐ๋ฆฌ๊ฐ€ ์ง์ ‘ ๋ฐœ๋ช…ํ•˜๊ณ  ๋งŒ๋“  ํ‡ด์‚ฌ๋Ÿ‰ ์ธก์ •๊ธฐ๋กœ
07:17
with a custom sediment sampler we've invented and built.
138
437880
3456
์นจ์ „๋ฌผ์„ ์ˆ˜์ง‘ํ–ˆ์Šต๋‹ˆ๋‹ค.
07:21
We pack the sediment into small bags,
139
441360
3256
์นจ์ „๋ฌผ์„ ์ž‘์€ ๋ด‰์ง€์— ๋‚˜๋ˆ  ๋‹ด์•„์„œ
07:24
we then dispatch them to hundreds of small bags
140
444640
2256
์ˆ˜๋ฐฑ ๊ฐœ์˜ ๋น„๋‹๋ฐฑ์œผ๋กœ ๋‹ค์‹œ ๋‚˜๋ˆ ๋‹ด์•„,
07:26
that we send to different universities,
141
446920
1936
๊ฐ๊ฐ ๋‹ค๋ฅธ ๋Œ€ํ•™์œผ๋กœ ๋ณด๋ƒˆ์Šต๋‹ˆ๋‹ค.
07:28
and we produce the map of the seabed radioactivity,
142
448880
2976
๊ทธ๋ฆฌ๊ณ  ํŠนํžˆ ๋ฌผ๊ณ ๊ธฐ๋“ค์ด ๋ฒˆ์‹ํ•˜๋Š” ์–ด๊ท€๋ฅผ ๊ณ ๋ คํ•œ
07:31
especially in estuaries where the fish will reproduce,
143
451880
2536
ํ•ด์ €์˜ ๋ฐฉ์‚ฌ๋Šฅ์„ ๋ณด์—ฌ์ฃผ๋Š” ์ง€๋„๋ฅผ ๋งŒ๋“ค์—ˆ์Šต๋‹ˆ๋‹ค.
07:34
and I will hope that we will have improved
144
454440
2056
์ง€์—ญ ์–ด๋ถ€๋“ค๊ณผ ์—ฌ๋Ÿฌ๋ถ„์ด ์ข‹์•„ํ•˜๋Š” ์ดˆ๋ฐฅ์˜ ์•ˆ์ „์„
07:36
the safety of the local fishermen and of your favorite sushi.
145
456520
3096
๊ฐœ์„ ํ•˜๋Š” ๋ฐ ๋„์›€์ด ๋˜์—ˆ๊ธฐ๋ฅผ ๋ฐ”๋ž๋‹ˆ๋‹ค.
07:39
(Laughter)
146
459640
1296
(์›ƒ์Œ)
07:40
You can see a progression here --
147
460960
1576
์ด ๊ณผ์ •์„ ๋ณด๋ฉด,
07:42
we've gone from a local problem to a remote problem to a global problem.
148
462560
4536
์šฐ๋ฆฌ๋Š” ์ง€์—ญ์‚ฌํšŒ์˜ ๋ฌธ์ œ์—์„œ ๋” ๋จผ ๊ณณ, ์„ธ๊ณ„์  ๋ฌธ์ œ๋กœ ๊ฐ”์Šต๋‹ˆ๋‹ค.
07:47
And it's been super exciting to work at these different scales,
149
467120
2953
์•„์ฃผ ๋‹จ์ˆœํ•˜๊ณ  ๊ณต๊ฐœ๋œ ๊ธฐ์ˆ ๋กœ ๋‹ค์–‘ํ•œ ํฌ๊ธฐ์˜ ๋ฌธ์ œ๋“ค์„
07:50
with also very simple, open-source technologies.
150
470097
3559
ํ•ด๊ฒฐํ•˜๋ ค๊ณ  ๋…ธ๋ ฅํ•˜๋Š” ๊ฒƒ์€ ๋ฉ”์šฐ ์‹ ๋‚˜๋Š” ์ผ์ž…๋‹ˆ๋‹ค.
07:53
But at the same time, it's been increasingly frustrating
151
473680
3336
ํ•˜์ง€๋งŒ ๋™์‹œ์— ๋งค์šฐ ์ขŒ์ ˆ๊ฐ์„ ๋Š๋ผ๊ฒŒ ํ•˜๋Š”๋ฐ
07:57
because we have only started to measure the damage that we have done.
152
477040
3696
์šฐ๋ฆฌ๊ฐ€ ์ดˆ๋ž˜ํ•œ ํ”ผํ•ด๋ฅผ ์ธก์ •ํ•˜๊ธฐ ์‹œ์ž‘ํ•œ ๊ฒƒ์— ๋ถˆ๊ณผํ•˜๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค.
08:00
We haven't even started to try to solve the problems.
153
480760
4080
์šฐ๋ฆฌ๋Š” ์•„์ง ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๋ ค๊ณ  ์‹œ์ž‘์กฐ์ฐจ ํ•˜์ง€ ์•Š์•˜์Šต๋‹ˆ๋‹ค.
08:05
And so I wonder if we should just take a leap
154
485640
2776
๊ทธ๋ž˜์„œ ์ €๋Š” ์šฐ๋ฆฌ๊ฐ€ ๊ทธ๋ƒฅ ํฐ ๊ฑธ์Œ์„ ๋‚ด๋”›์–ด
08:08
and try to invent better ways to do all these things.
155
488440
4640
์ด๋Ÿฐ ์ผ๋“ค์„ ํ•˜๋Š” ๋ฐ ๋” ๋‚˜์€ ๋ฐฉ๋ฒ•์„ ๋ฐœ๋ช…ํ•ด์•ผ ํ•˜๋Š” ๊ฒƒ์ธ์ง€ ๊ถ๊ธˆํ–ˆ์Šต๋‹ˆ๋‹ค.
08:13
And so the classroom started to feel a little bit small,
156
493520
3576
๊ทธ๋ž˜์„œ ๊ต์‹ค์ด ์ž‘๊ฒŒ ๋Š๊ปด์ง€๊ธฐ ์‹œ์ž‘ํ–ˆ๊ณ 
08:17
so we found an industrial site in Hong Kong,
157
497120
2696
์šฐ๋ฆฌ๋Š” ํ™์ฝฉ์— ์žˆ๋Š” ์‚ฐ์—…๋ถ€์ง€๋ฅผ ์ฐพ์•„๋‚ด์–ด
08:19
and we turned it into the largest mega-space
158
499840
3256
์‚ฌํšŒ์™€ ํ™˜๊ฒฝ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์— ์ง‘์ค‘ํ•˜๋Š”
08:23
focused on social and environmental impact.
159
503120
3176
์—„์ฒญ๋‚˜๊ฒŒ ํฐ ๊ณต๊ฐ„์œผ๋กœ ๋งŒ๋“ค์—ˆ์Šต๋‹ˆ๋‹ค.
08:26
It's in central Hong Kong,
160
506320
1296
์ด๊ณณ์€ ํ™์ฝฉ์˜ ์ค‘์‹ฌ๋ถ€์— ์žˆ๋Š”๋ฐ
08:27
and it's a place we can work with wood, metal, chemistry,
161
507640
3216
๋‚˜๋ฌด๋‚˜ ์‡ , ํ™”ํ•™๊ณผ ์•ฝ๊ฐ„์˜ ์ƒ๋ฌผํ•™๊ณผ ๊ด‘ํ•™์„ ์ด์šฉํ•ด์„œ
08:30
a bit of biology, a bit of optics,
162
510880
1626
์ž‘์—…์„ ํ•  ์ˆ˜ ์žˆ๋Š” ๊ณณ์ž…๋‹ˆ๋‹ค.
08:32
basically you can build pretty much everything there.
163
512530
2492
๊ฑฐ์˜ ๋ชจ๋“  ๊ฒƒ์„ ๋‹ค ๋งŒ๋“ค ์ˆ˜ ์žˆ๋Š” ๊ณณ์ด์ฃ .
08:35
And its a place where adults and kids can play together.
164
515047
2969
์–ด๋ฅธ๊ณผ ์•„์ด๊ฐ€ ๊ฐ™์ด ๋†€ ์ˆ˜ ์žˆ๋Š” ๊ณณ์ด๊ธฐ๋„ ํ•ฉ๋‹ˆ๋‹ค.
08:38
It's a place where kids' dreams can come true,
165
518040
3576
์–ด๋ฅธ๋“ค์˜ ๋„์›€์œผ๋กœ ์•„์ด๋“ค์ด
08:41
with the help of adults,
166
521640
1336
๊ฟˆ์„ ์ด๋ฃฐ ์ˆ˜ ์žˆ๋Š” ๊ณณ์ด์ž,
08:43
and where adults can be kids again.
167
523000
1816
์–ด๋ฅธ๋“ค์ด ์•„์ด๋กœ ๋Œ์•„๊ฐˆ ์ˆ˜ ์žˆ๋Š” ๊ณณ์ž…๋‹ˆ๋‹ค.
08:44
Student: Acceleration! Acceleration!
168
524840
3136
์•„์ด: ๋” ๋น ๋ฅด๊ฒŒ! ๋” ๋น ๋ฅด๊ฒŒ!
08:48
Cesar Harada: We're asking questions such as,
169
528000
2135
์˜ˆ๋ฅผ ๋“ค์–ด, ์‹ ์žฌ์ƒ์—๋„ˆ์ง€๋กœ
08:50
can we invent the future of mobility with renewable energy?
170
530159
2817
๋ฏธ๋ž˜์˜ ์ด๋™์ˆ˜๋‹จ์„ ๋ฐœ๋ช…ํ•  ์ˆ˜ ์žˆ์„๊นŒ? ์™€ ๊ฐ™์€
08:53
For example.
171
533000
1200
์งˆ๋ฌธ์„ ํ•ฉ๋‹ˆ๋‹ค.
08:55
Or, can we help the mobility of the aging population
172
535320
4296
์•„๋‹ˆ๋ฉด ๊ณ ๋ น์ธต์˜ ์ด๋™์„ฑ์„
08:59
by transforming very standard wheelchairs into cool, electric vehicles?
173
539640
4400
ํ‰๋ฒ”ํ•œ ํœ ์ฒด์–ด๋ฅผ ๋ฉ‹์ง„ ์ „๊ธฐ๋™๋ ฅ์ฐจ๋กœ ๋ณ€ํ˜•์‹œ์ผœ ํ–ฅ์ƒ์‹œํ‚ฌ ์ˆ˜ ์žˆ์„๊นŒ?
09:05
So plastic, oil and radioactivity are horrible, horrible legacies,
174
545240
6536
ํ”Œ๋ผ์Šคํ‹ฑ๊ณผ ๊ธฐ๋ฆ„, ๋ฐฉ์‚ฌ๋Šฅ์€ ๋ฌผ๋ ค์ฃผ๊ธฐ์— ๋”์ฐํ•œ ์œ ์‚ฐ์ž…๋‹ˆ๋‹ค.
09:11
but the very worst legacy that we can leave our children is lies.
175
551800
4520
ํ•˜์ง€๋งŒ ๊ทธ ์ค‘ ์•„์ด๋“ค์—๊ฒŒ ๋ฌผ๋ ค์ค„ ์ˆ˜ ์žˆ๋Š” ์ตœ์•…์˜ ์œ ์‚ฐ์€ ๊ฑฐ์ง“๋ง์ž…๋‹ˆ๋‹ค.
09:16
We can no longer afford to shield the kids from the ugly truth
176
556760
5216
์šฐ๋ฆฌ๋Š” ๋” ์ด์ƒ ์ถ”ํ•œ ์ง„์‹ค๋กœ๋ถ€ํ„ฐ ์•„์ด๋“ค์„ ๋ณดํ˜ธํ•  ์ˆ˜ ์—†์Šต๋‹ˆ๋‹ค.
09:22
because we need their imagination to invent the solutions.
177
562000
3920
์šฐ๋ฆฌ์—๊ฒ ํ•ด๊ฒฐ์ฑ…์„ ๋ฐœ๋ช…ํ•˜๊ธฐ ์œ„ํ•ด ์•„์ด๋“ค์˜ ์ƒ์ƒ๋ ฅ์ด ํ•„์š”ํ•˜๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค.
09:26
So citizen scientists, makers, dreamers --
178
566720
4976
์‹œ๋ฏผ ๊ณผํ•™์ž์™€ ๋ฐœ๋ช…๊ฐ€, ๊ณต์ƒ๊ฐ€ ์—ฌ๋Ÿฌ๋ถ„..
09:31
we must prepare the next generation
179
571720
2696
์šฐ๋ฆฌ๋Š” ๋‹ค์Œ ์„ธ๋Œ€๊ฐ€
09:34
that cares about the environment and people,
180
574440
3056
ํ™˜๊ฒฝ๊ณผ ์‚ฌ๋žŒ๋“ค์— ๊ด€์‹ฌ์„ ๊ฐ€์ง€๊ณ 
09:37
and that can actually do something about it.
181
577520
2200
์‹ค์ œ๋กœ ํ–‰๋™์— ์˜ฎ๊ธฐ๋„๋ก ์ค€๋น„์‹œ์ผœ์•ผ ํ•ฉ๋‹ˆ๋‹ค.
09:40
Thank you.
182
580200
1216
๊ฐ์‚ฌํ•ฉ๋‹ˆ๋‹ค.
09:41
(Applause)
183
581440
3160
(๋ฐ•์ˆ˜)
์ด ์›น์‚ฌ์ดํŠธ ์ •๋ณด

์ด ์‚ฌ์ดํŠธ๋Š” ์˜์–ด ํ•™์Šต์— ์œ ์šฉํ•œ YouTube ๋™์˜์ƒ์„ ์†Œ๊ฐœํ•ฉ๋‹ˆ๋‹ค. ์ „ ์„ธ๊ณ„ ์ตœ๊ณ ์˜ ์„ ์ƒ๋‹˜๋“ค์ด ๊ฐ€๋ฅด์น˜๋Š” ์˜์–ด ์ˆ˜์—…์„ ๋ณด๊ฒŒ ๋  ๊ฒƒ์ž…๋‹ˆ๋‹ค. ๊ฐ ๋™์˜์ƒ ํŽ˜์ด์ง€์— ํ‘œ์‹œ๋˜๋Š” ์˜์–ด ์ž๋ง‰์„ ๋”๋ธ” ํด๋ฆญํ•˜๋ฉด ๊ทธ๊ณณ์—์„œ ๋™์˜์ƒ์ด ์žฌ์ƒ๋ฉ๋‹ˆ๋‹ค. ๋น„๋””์˜ค ์žฌ์ƒ์— ๋งž์ถฐ ์ž๋ง‰์ด ์Šคํฌ๋กค๋ฉ๋‹ˆ๋‹ค. ์˜๊ฒฌ์ด๋‚˜ ์š”์ฒญ์ด ์žˆ๋Š” ๊ฒฝ์šฐ ์ด ๋ฌธ์˜ ์–‘์‹์„ ์‚ฌ์šฉํ•˜์—ฌ ๋ฌธ์˜ํ•˜์‹ญ์‹œ์˜ค.

https://forms.gle/WvT1wiN1qDtmnspy7