ABOUT THE SPEAKER
Hans Rosling - Global health expert; data visionary
In Hans Rosling’s hands, data sings. Global trends in health and economics come to vivid life. And the big picture of global development—with some surprisingly good news—snaps into sharp focus.

Why you should listen

Even the most worldly and well-traveled among us have had their perspectives shifted by Hans Rosling. A professor of global health at Sweden's Karolinska Institute, his work focused on dispelling common myths about the so-called developing world, which (as he pointed out) is no longer worlds away from the West. In fact, most of the Third World is on the same trajectory toward health and prosperity, and many countries are moving twice as fast as the west did.

What set Rosling apart wasn't just his apt observations of broad social and economic trends, but the stunning way he presented them. Guaranteed: You've never seen data presented like this. A presentation that tracks global health and poverty trends should be, in a word: boring. But in Rosling's hands, data sings. Trends come to life. And the big picture — usually hazy at best — snaps into sharp focus.

Rosling's presentations were grounded in solid statistics (often drawn from United Nations and World Bank data), illustrated by the visualization software he developed. The animations transform development statistics into moving bubbles and flowing curves that make global trends clear, intuitive and even playful. During his legendary presentations, Rosling took this one step farther, narrating the animations with a sportscaster's flair.

Rosling developed the breakthrough software behind his visualizations through his nonprofit Gapminder, founded with his son and daughter-in-law. The free software — which can be loaded with any data — was purchased by Google in March 2007. (Rosling met the Google founders at TED.)

Rosling began his wide-ranging career as a physician, spending many years in rural Africa tracking a rare paralytic disease (which he named konzo) and discovering its cause: hunger and badly processed cassava. He co-founded Médecins sans Frontièrs (Doctors without Borders) Sweden, wrote a textbook on global health, and as a professor at the Karolinska Institut in Stockholm initiated key international research collaborations. He's also personally argued with many heads of state, including Fidel Castro.

Hans Rosling passed away in February 2017. He is greatly missed.


More profile about the speaker
Hans Rosling | Speaker | TED.com
TED2006

Hans Rosling: The best stats you've ever seen

汉斯罗斯林用前所未有的好方法诠释数字统计

Filmed:
14,386,844 views

你肯定没有看过这样的数据演示。如解说体育比赛实况一般的生动与紧张,统计大师汉斯罗斯林将颠覆所谓 “发展中国家” 这一理念。
- Global health expert; data visionary
In Hans Rosling’s hands, data sings. Global trends in health and economics come to vivid life. And the big picture of global development—with some surprisingly good news—snaps into sharp focus. Full bio

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

00:25
About 10 years年份 ago, I took on the task任务 to teach global全球 development发展
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大约在十年前, 我担当起
00:29
to Swedish瑞典 undergraduate大学本科 students学生们. That was after having spent花费
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给瑞典大学生讲授全球发展的任务
00:33
about 20 years年份 together一起 with African非洲人 institutions机构 studying研究 hunger饥饿 in Africa非洲,
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之前的20年我一直在非洲研究饥饿问题
00:37
so I was sort分类 of expected预期 to know a little about the world世界.
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所以大家以为我对世界有些了解
00:41
And I started开始 in our medical university大学, Karolinska卡罗林斯卡 Institute研究所,
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在我们的卡罗林斯卡医学院
00:46
an undergraduate大学本科 course课程 called Global全球 Health健康. But when you get
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我开设了一门本科生课程“全球健康”
00:50
that opportunity机会, you get a little nervous紧张. I thought, these students学生们
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刚开课的时候我还有些紧张
00:53
coming未来 to us actually其实 have the highest最高 grade年级 you can get
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因为来听课的都是瑞典大学的优等生
00:56
in Swedish瑞典 college学院 systems系统 -- so, I thought, maybe they know everything
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他们或许早已了解我准备教的内容
00:59
I'm going to teach them about. So I did a pre-test预测试 when they came来了.
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于是在第一堂课里,我作了一个小测试
01:03
And one of the questions问题 from which哪一个 I learned学到了 a lot was this one:
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其中有一道题让我受益匪浅
01:06
"Which哪一个 country国家 has the highest最高 child儿童 mortality死亡 of these five pairs?"
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下列5对国家中,哪一个的儿童死亡率高于另一个?
01:10
And I put them together一起, so that in each pair of country国家,
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我所选择的配对国家都是
01:14
one has twice两次 the child儿童 mortality死亡 of the other. And this means手段 that
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一个的儿童死亡率是另一个的两倍,因为数据差距很大
01:19
it's much bigger a difference区别 than the uncertainty不确定 of the data数据.
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因此数据本身的不确定性可以忽略不计
01:24
I won't惯于 put you at a test测试 here, but it's Turkey火鸡,
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今天我不会拿这来考大家
01:26
which哪一个 is highest最高 there, Poland波兰, Russia俄国, Pakistan巴基斯坦 and South Africa非洲.
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土耳其,波兰,俄罗斯,巴基斯坦和南非
01:31
And these were the results结果 of the Swedish瑞典 students学生们. I did it so I got
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这是瑞典学生的测验结果
01:34
the confidence置信度 interval间隔, which哪一个 is pretty漂亮 narrow狭窄, and I got happy快乐,
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让我高兴的是
01:37
of course课程: a 1.8 right answer回答 out of five possible可能. That means手段 that
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5题中平均答对的只有1.8题
01:41
there was a place地点 for a professor教授 of international国际 health健康 --
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我这个教授还有这门课
01:44
(Laughter笑声) and for my course课程.
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因此都有了存在的必要
01:46
But one late晚了 night, when I was compiling编译 the report报告
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但后来有天深夜,当我写总结报告的时候
01:50
I really realized实现 my discovery发现. I have shown显示
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我突然有了新的发现
01:54
that Swedish瑞典 top最佳 students学生们 know statistically统计学 significantly显著 less
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瑞典大学的优等生们对世界的了解
01:59
about the world世界 than the chimpanzees黑猩猩.
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竟然还不如黑猩猩
02:01
(Laughter笑声)
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(笑声)
02:03
Because the chimpanzee黑猩猩 would score得分了 half right if I gave them
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因为黑猩猩们至少能蒙对一半
02:07
two bananas香蕉 with Sri斯里兰卡 Lanka斯里兰卡 and Turkey火鸡. They would be right half of the cases.
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在两个选项旁边各放一根香蕉,就有一半的几率答对。
02:10
But the students学生们 are not there. The problem问题 for me was not ignorance无知;
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这些优等生们却做不到。这不是由于知识缺乏
02:14
it was preconceived先入为主 ideas思路.
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而是他们先入为主的错误理念
02:17
I did also an unethical不道德的 study研究 of the professors教授 of the Karolinska卡罗林斯卡 Institute研究所
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我还把这个测试拿去 给卡罗林斯卡学院的教授们做
02:21
(Laughter笑声)
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(笑声)
02:22
-- that hands out the Nobel诺贝尔 Prize in Medicine医学,
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他们每年负责颁发诺贝尔医学奖
02:24
and they are on par平价 with the chimpanzee黑猩猩 there.
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结果教授们和黑猩猩半斤八两
02:26
(Laughter笑声)
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(笑声)
02:29
This is where I realized实现 that there was really a need to communicate通信,
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我意识到很有必要交流一下这个问题
02:33
because the data数据 of what's happening事件 in the world世界
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因为多数人并不知道
02:36
and the child儿童 health健康 of every一切 country国家 is very well aware知道的.
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世界各国的儿童健康的改善
02:39
We did this software软件 which哪一个 displays显示器 it like this: every一切 bubble泡沫 here is a country国家.
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我们作了一个软件,每一个小球代表一个国家
02:44
This country国家 over here is China中国. This is India印度.
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这个是中国,这个是印度
02:50
The size尺寸 of the bubble泡沫 is the population人口, and on this axis here I put fertility生育能力 rate.
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小球的尺寸代表该国的人口,X轴是生育率
02:56
Because my students学生们, what they said
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我曾问过学生们
02:59
when they looked看着 upon the world世界, and I asked them,
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如果让你们来审视这个世界
03:01
"What do you really think about the world世界?"
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你们的真实想法是什么
03:03
Well, I first discovered发现 that the textbook教科书 was Tintin丁丁, mainly主要.
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其实这些教科书上都是丁丁历险记(带有殖民主义思想的漫画)的人物
03:07
(Laughter笑声)
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(笑声)
03:08
And they said, "The world世界 is still 'we''我们' and 'them'他们.'
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学生们回答 世界是由“我们和他们”组成的
03:11
And we is Western西 world世界 and them is Third第三 World世界."
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“我们”指西方世界 “他们”指第三世界
03:14
"And what do you mean with Western西 world世界?" I said.
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我又问 “什么是西方世界?”
03:17
"Well, that's long life and small family家庭, and Third第三 World世界 is short life and large family家庭."
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“西方世界寿命长且家庭小; 第三世界寿命短而家庭大。”
03:22
So this is what I could display显示 here. I put fertility生育能力 rate here: number of children孩子 per woman女人:
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那么一起来看看 X轴是生育率,每个妇女的育儿数
03:28
one, two, three, four, up to about eight children孩子 per woman女人.
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从每人1,2,3,4胎,到8胎
03:32
We have very good data数据 since以来 1962 -- 1960 about -- on the size尺寸 of families家庭 in all countries国家.
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我们有1962年之后的各国家庭大小的可靠数据
03:38
The error错误 margin余量 is narrow狭窄. Here I put life expectancy期待 at birth分娩,
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数据误差相当小。Y轴是平均寿命
03:41
from 30 years年份 in some countries国家 up to about 70 years年份.
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从30岁到70岁不等
03:45
And 1962, there was really a group of countries国家 here
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1962年的时候 的确有一群国家在上面
03:48
that was industrialized工业化 countries国家, and they had small families家庭 and long lives生活.
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这些是发达国家,他们家庭小,寿命长
03:53
And these were the developing发展 countries国家:
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而这些则是发展中国家
03:55
they had large families家庭 and they had relatively相对 short lives生活.
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他们家庭大,寿命也相对短些
03:58
Now what has happened发生 since以来 1962? We want to see the change更改.
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从1962年到今天 世界有什么变化吗?
04:02
Are the students学生们 right? Is it still two types类型 of countries国家?
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我们来看看 学生们正确吗?国家还是分为2类吗?
04:06
Or have these developing发展 countries国家 got smaller families家庭 and they live生活 here?
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或者发展中国家的家庭变小(这些小球)移动到了左边?
04:09
Or have they got longer lives生活 and live生活 up there?
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或者发展中国家人们的寿命变长(这些小球)移动到了上面?
04:11
Let's see. We stopped停止 the world世界 then. This is all U.N. statistics统计
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这些数据都来自于联合国
04:14
that have been available可得到. Here we go. Can you see there?
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大家看到没有?
04:17
It's China中国 there, moving移动 against反对 better health健康 there, improving提高 there.
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这个是中国,他们在往上移动,健康状况不断改善
04:20
All the green绿色 Latin拉丁 American美国 countries国家 are moving移动 towards smaller families家庭.
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这些绿色的拉丁美洲国家 正朝向小家庭的方向移动
04:23
Your yellow黄色 ones那些 here are the Arabic阿拉伯 countries国家,
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这些黄色的小球是阿拉伯国家
04:26
and they get larger families家庭, but they -- no, longer life, but not larger families家庭.
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寿命在变长但家庭规模不变
04:30
The Africans非洲人 are the green绿色 down here. They still remain here.
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非洲国家是下面的绿球,他们一直在下面
04:33
This is India印度. Indonesia's印尼 moving移动 on pretty漂亮 fast快速.
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这个是印度 印度尼西亚的移动速度非常快
04:36
(Laughter笑声)
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(笑声)
04:37
And in the '80s here, you have Bangladesh孟加拉国 still among其中 the African非洲人 countries国家 there.
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80年代的时候 孟加拉国仍然和非洲国家在一起
04:40
But now, Bangladesh孟加拉国 -- it's a miracle奇迹 that happens发生 in the '80s:
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但是80年代的奇迹发生在孟加拉国
04:43
the imams伊玛目 start开始 to promote促进 family家庭 planning规划.
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妈妈们开始宣传和普及计划生育
04:46
They move移动 up into that corner. And in '90s, we have the terrible可怕 HIVHIV epidemic疫情
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他们向左上角移动 90年代恐怖的艾滋病流行
04:51
that takes down the life expectancy期待 of the African非洲人 countries国家
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导致非洲国家的平均寿命缩短
04:54
and all the rest休息 of them move移动 up into the corner,
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而其他国家都向左上角移动
04:58
where we have long lives生活 and small family家庭, and we have a completely全然 new world世界.
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大家都有了长寿命和小家庭,而世界也焕然一新了
05:02
(Applause掌声)
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(掌声)
05:15
Let me make a comparison对照 directly between之间 the United联合的 States状态 of America美国 and Vietnam越南.
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现在我们对比一下美国和越南
05:20
1964: America美国 had small families家庭 and long life;
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1964年的美国家庭小寿命长
05:25
Vietnam越南 had large families家庭 and short lives生活. And this is what happens发生:
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越南的家庭大而寿命短。这是后来的变化
05:29
the data数据 during the war战争 indicate表明 that even with all the death死亡,
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越战时期的数据显示,尽管战争造成伤亡
05:35
there was an improvement起色 of life expectancy期待. By the end结束 of the year,
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越南人的平均寿命仍有提高
05:38
the family家庭 planning规划 started开始 in Vietnam越南 and they went for smaller families家庭.
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70年代末期 越南的计划生育减小了家庭规模
05:41
And the United联合的 States状态 up there is getting得到 for longer life,
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美国人的平均寿命也在延长
05:44
keeping保持 family家庭 size尺寸. And in the '80s now,
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而家庭规模不变
05:47
they give up communist共产 planning规划 and they go for market市场 economy经济,
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到了90年代 越南由计划经济转为市场经济
05:50
and it moves移动 faster更快 even than social社会 life. And today今天, we have
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其经济发展的速度超过了社会的发展
05:54
in Vietnam越南 the same相同 life expectancy期待 and the same相同 family家庭 size尺寸
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今天(2003)越南人的平均寿命和家庭规模
05:59
here in Vietnam越南, 2003, as in United联合的 States状态, 1974, by the end结束 of the war战争.
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已经和越战结束时(1974)的美国一样
06:06
I think we all -- if we don't look in the data数据 --
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如果没有看到这些数据的话
06:10
we underestimate低估 the tremendous巨大 change更改 in Asia亚洲, which哪一个 was
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我们会低估了亚洲的巨大变化
06:14
in social社会 change更改 before we saw the economical经济 change更改.
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这些超前于经济发展的社会变革
06:18
Let's move移动 over to another另一个 way here in which哪一个 we could display显示
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下面我们换个视角
06:23
the distribution分配 in the world世界 of the income收入. This is the world世界 distribution分配 of income收入 of people.
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X轴显示了全世界的收入分布
06:30
One dollar美元, 10 dollars美元 or 100 dollars美元 per day.
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每天收入1美元,10美元和100美元
06:35
There's no gap间隙 between之间 rich丰富 and poor较差的 any longer. This is a myth神话.
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富与穷之间的鸿沟几乎消失了,简直是个奇迹
06:39
There's a little hump驼峰 here. But there are people all the way.
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这里还有一个很小的峰,但总体上是均数分布的
06:44
And if we look where the income收入 ends结束 up -- the income收入 --
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我们看看收入的分配情况
06:48
this is 100 percent百分 the world's世界 annual全年 income收入. And the richest首富 20 percent百分,
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这代表全世界人民每年的全部收入
06:54
they take out of that about 74 percent百分. And the poorest最穷 20 percent百分,
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最富有的20%那部分人
得到了全部收入的74%
07:01
they take about two percent百分. And this shows节目 that the concept概念
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最贫穷的20%那部分人 只得到2%
07:06
of developing发展 countries国家 is extremely非常 doubtful. We think about aid援助, like
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可见发展中国家的理念 极其的不确切
07:10
these people here giving aid援助 to these people here. But in the middle中间,
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我们总以为最富的人应该给最穷的人提供援助
07:15
we have most the world世界 population人口, and they have now 24 percent百分 of the income收入.
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其实中间这部分才是世界人口的主体 而他们仅得到全部收入的24%
07:19
We heard听说 it in other forms形式. And who are these?
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这是个老问题了,中间这些人是谁?
07:23
Where are the different不同 countries国家? I can show显示 you Africa非洲.
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他们在哪些国家?先看非洲
07:27
This is Africa非洲. 10 percent百分 the world世界 population人口, most in poverty贫穷.
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非洲占世界人口的十分之一,多数是穷人
07:32
This is OECD经合组织. The rich丰富 country国家. The country国家 club俱乐部 of the U.N.
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这个代表富裕的经合组织成员国,联合国俱乐部的会员
07:37
And they are over here on this side. Quite相当 an overlap交叠 between之间 Africa非洲 and OECD经合组织.
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他们在这边,很小一部分与非洲重叠
07:42
And this is Latin拉丁 America美国. It has everything on this Earth地球,
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这是拉丁美洲,他们可以代表全世界
07:45
from the poorest最穷 to the richest首富, in Latin拉丁 America美国.
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从最贫穷到最富有的人都在那里
07:48
And on top最佳 of that, we can put East Europe欧洲, we can put East Asia亚洲,
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再往上是东欧,东亚还有南亚
07:53
and we put South Asia亚洲. And how did it look like if we go back in time,
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过去是什么样子的呢?
07:58
to about 1970? Then there was more of a hump驼峰.
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如果我们回到1970年,这里有一个明显的峰
08:03
And we have most who lived生活 in absolute绝对 poverty贫穷 were Asians亚洲人.
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这些绝对贫困的人群中 大多数是亚洲人
08:07
The problem问题 in the world世界 was the poverty贫穷 in Asia亚洲. And if I now let the world世界 move移动 forward前锋,
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那时世界的问题就在于亚洲的贫穷
08:14
you will see that while population人口 increase增加, there are
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后来随着人口的增长
08:17
hundreds数以百计 of millions百万 in Asia亚洲 getting得到 out of poverty贫穷 and some others其他
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数以亿计的亚洲人摆脱了贫困
08:20
getting得到 into poverty贫穷, and this is the pattern模式 we have today今天.
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另外一些人却陷入贫穷,这就是今天的世界
08:23
And the best最好 projection投影 from the World世界 Bank银行 is that this will happen发生,
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而这是世界银行对未来最乐观的预测
08:27
and we will not have a divided分为 world世界. We'll have most people in the middle中间.
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世界再也不是贫富悬殊的,大多数人拥有中等的收入
08:31
Of course课程 it's a logarithmic对数的 scale规模 here,
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当然这是指数幂分布的图
08:33
but our concept概念 of economy经济 is growth发展 with percent百分. We look upon it
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因为经济的增长是用百分比来衡量的
08:38
as a possibility可能性 of percentile百分 increase增加. If I change更改 this, and I take
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我们用百分比的变化来评估经济增长
08:44
GDPGDP per capita人头 instead代替 of family家庭 income收入, and I turn these
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下面把X轴改为人均国内生产总值
08:48
individual个人 data数据 into regional区域性 data数据 of gross domestic国内 product产品,
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个人的数据转为各大洲的数据
08:54
and I take the regions地区 down here, the size尺寸 of the bubble泡沫 is still the population人口.
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球的大小代表人口的多少
08:58
And you have the OECD经合组织 there, and you have sub-Saharan撒哈拉以南 Africa非洲 there,
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这个是经合组织国家,这是撒哈拉以南非洲
09:01
and we take off the Arab阿拉伯 states状态 there,
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我们把阿拉伯国家
09:04
coming未来 both from Africa非洲 and from Asia亚洲, and we put them separately分别,
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从非洲和亚洲单独分出来
09:08
and we can expand扩大 this axis, and I can give it a new dimension尺寸 here,
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然后把X轴延伸一下 再加上一个新的维度
09:13
by adding加入 the social社会 values there, child儿童 survival生存.
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一个有社会价值的参数 儿童生存率
09:16
Now I have money on that axis, and I have the possibility可能性 of children孩子 to survive生存 there.
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X轴代表经济 Y轴显示儿童存活的比率
09:21
In some countries国家, 99.7 percent百分 of children孩子 survive生存 to five years年份 of age年龄;
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一些国家的99.7%的小孩 可以活到5岁以上
09:25
others其他, only 70. And here it seems似乎 there is a gap间隙
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另一些国家只有70% 很明显可以看到
09:29
between之间 OECD经合组织, Latin拉丁 America美国, East Europe欧洲, East Asia亚洲,
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经合组织成员国 和拉丁美洲,东欧,东亚
09:33
Arab阿拉伯 states状态, South Asia亚洲 and sub-Saharan撒哈拉以南 Africa非洲.
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阿拉伯国家,南亚 以及撒哈拉以南非洲地区的差距
09:37
The linearity线性 is very strong强大 between之间 child儿童 survival生存 and money.
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儿童生存率和经济之间 联系非常紧密
09:42
But let me split分裂 sub-Saharan撒哈拉以南 Africa非洲. Health健康 is there and better health健康 is up there.
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下面把撒哈拉以南非洲地区 分解成各个国家
09:50
I can go here and I can split分裂 sub-Saharan撒哈拉以南 Africa非洲 into its countries国家.
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分布靠上边的国家 拥有更高的健康水平
09:55
And when it burst爆裂, the size尺寸 of its country国家 bubble泡沫 is the size尺寸 of the population人口.
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撒哈拉以南的非洲各国是如此分布的 小球的尺寸代表该国人口
10:00
Sierra内华达 Leone塞拉利昂 down there. Mauritius毛里求斯 is up there. Mauritius毛里求斯 was the first country国家
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塞拉里昂在下边 毛里求斯在上边
10:04
to get away with trade贸易 barriers障碍, and they could sell their sugar --
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毛里求斯是第一个消除了贸易壁垒的国家
10:08
they could sell their textiles纺织品 -- on equal等于 terms条款 as the people in Europe欧洲 and North America美国.
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他们的蔗糖和纺织品的贸易协定 与欧洲和北美一样
10:13
There's a huge巨大 difference区别 between之间 Africa非洲. And Ghana加纳 is here in the middle中间.
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但是非洲内部的差异非常巨大 加纳在中部
10:17
In Sierra内华达 Leone塞拉利昂, humanitarian人道主义 aid援助.
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塞拉里昂需要人道主义援助
10:20
Here in Uganda乌干达, development发展 aid援助. Here, time to invest投资; there,
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乌干达则需要发展援助 在加纳可以进行投资了
10:25
you can go for a holiday假日. It's a tremendous巨大 variation变异
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毛里求斯则可以去度假 非洲内部的差异之大确实很惊人
10:28
within Africa非洲 which哪一个 we rarely很少 often经常 make -- that it's equal等于 everything.
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而我们却总以为 非洲国家都差不多
10:33
I can split分裂 South Asia亚洲 here. India's印度 the big bubble泡沫 in the middle中间.
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下面分解南亚各国 印度是中间的蓝色大球
10:37
But a huge巨大 difference区别 between之间 Afghanistan阿富汗 and Sri斯里兰卡 Lanka斯里兰卡.
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而斯里兰卡和阿富汗有着巨大差异
10:41
I can split分裂 Arab阿拉伯 states状态. How are they? Same相同 climate气候, same相同 culture文化,
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把阿拉伯世界分解来看 尽管是相同的气候,相同的文化
10:45
same相同 religion宗教 -- huge巨大 difference区别. Even between之间 neighbors邻居.
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相同的宗教 却有巨大的差异
10:49
Yemen也门, civil国内 war战争. United联合的 Arab阿拉伯 Emirate酋长国, money which哪一个 was quite相当 equally一样 and well used.
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也门在打内战 邻国阿联酋却躺在钱堆里
10:54
Not as the myth神话 is. And that includes包括 all the children孩子 of the foreign国外 workers工人 who are in the country国家.
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而且(阿联酋的)儿童健康数据 包含了所有的外籍劳工
11:01
Data数据 is often经常 better than you think. Many许多 people say data数据 is bad.
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大家总说数据不准确 数据其实比我们想象的好很多
11:06
There is an uncertainty不确定 margin余量, but we can see the difference区别 here:
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数据是有误差
11:08
Cambodia柬埔寨, Singapore新加坡. The differences分歧 are much bigger
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但柬埔寨和新加坡的差距肯定远大于数据的误差
11:11
than the weakness弱点 of the data数据. East Europe欧洲:
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再看东欧
11:14
Soviet苏联 economy经济 for a long time, but they come out after 10 years年份
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在苏联经济模式下发展了多年 但在过去10年
11:20
very, very differently不同. And there is Latin拉丁 America美国.
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却经历了巨大的变化
11:23
Today今天, we don't have to go to Cuba古巴 to find a healthy健康 country国家 in Latin拉丁 America美国.
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当今的拉丁美洲 古巴再也不是唯一的健康国家了
11:27
Chile智利 will have a lower降低 child儿童 mortality死亡 than Cuba古巴 within some few少数 years年份 from now.
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几年后智利的儿童死亡率将低于古巴
11:32
And here we have high-income高收入 countries国家 in the OECD经合组织.
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这些是经合组织成员国
11:35
And we get the whole整个 pattern模式 here of the world世界,
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这里显示的就是我们的世界
11:39
which哪一个 is more or less like this. And if we look at it,
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大概就是这样的情形 如果我们回到过去
11:44
how it looks容貌 -- the world世界, in 1960, it starts启动 to move移动. 1960.
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看看世界是怎样的 从1960年开始
11:50
This is Mao Tse-tung谢彤. He brought health健康 to China中国. And then he died死亡.
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1960年(中国有)毛泽东 他给中国带来了健康
11:53
And then Deng Xiaoping小平 came来了 and brought money to China中国, and brought them into the mainstream主流 again.
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他去世后邓小平给中国带来了金钱 同时把中国带回到世界的主流当中
11:58
And we have seen看到 how countries国家 move移动 in different不同 directions方向 like this,
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其他国家的移动方向也不尽相同
12:02
so it's sort分类 of difficult to get
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很难找出哪个国家
12:06
an example country国家 which哪一个 shows节目 the pattern模式 of the world世界.
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能代表全世界的发展模式
12:11
But I would like to bring带来 you back to about here at 1960.
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我们回到1960年做个比较
12:17
I would like to compare比较 South Korea韩国, which哪一个 is this one, with Brazil巴西,
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先选中韩国(左边的小黄球)巴西(右边的黄绿色大球)
12:27
which哪一个 is this one. The label标签 went away for me here. And I would like to compare比较 Uganda乌干达,
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乌干达(Y轴上面的小红球)
12:32
which哪一个 is there. And I can run it forward前锋, like this.
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随着时间的推移,我们看到
12:37
And you can see how South Korea韩国 is making制造 a very, very fast快速 advancement进步,
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韩国的发展速度非常非常快
12:46
whereas Brazil巴西 is much slower比较慢.
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巴西就慢得多
12:49
And if we move移动 back again, here, and we put on trails步道 on them, like this,
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我们再回到过去 给每个球画出运动的轨迹
12:55
you can see again that the speed速度 of development发展
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可以看到,发展速度的差距非常大
12:59
is very, very different不同, and the countries国家 are moving移动 more or less
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虽然各国的经济和健康 发展的轨迹大同小异
13:05
in the same相同 rate as money and health健康, but it seems似乎 you can move移动
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但是健康水平起点较高的国家
13:09
much faster更快 if you are healthy健康 first than if you are wealthy富裕 first.
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发展速度远超过经济水平起点高的
13:14
And to show显示 that, you can put on the way of United联合的 Arab阿拉伯 Emirate酋长国.
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为了说明这一点 我们看看阿联酋
13:18
They came来了 from here, a mineral矿物 country国家. They cached缓存 all the oil;
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他们从这里出发 一个资源型国家
13:21
they got all the money; but health健康 cannot不能 be bought at the supermarket超级市场.
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他们靠石油大把赚钱 但健康绝不是超市里的货物
13:25
You have to invest投资 in health健康. You have to get kids孩子 into schooling教育.
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需要卫生方面的投资 需要提高儿童的教育水平
13:29
You have to train培养 health健康 staff员工. You have to educate教育 the population人口.
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需要培训卫生工作者 还要教育民众
13:32
And Sheikh谢赫 Sayed赛义德 did that in a fairly相当 good way.
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Sheikh Sayed 干的非常漂亮
13:35
In spite尽管 of falling落下 oil prices价格, he brought this country国家 up here.
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尽管油价下跌了 他仍改善了阿联酋的健康
13:39
So we've我们已经 got a much more mainstream主流 appearance出现 of the world世界,
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这里我们可以看到 世界发展的主流
13:43
where all countries国家 tend趋向 to use their money
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各国对资金的分配和使用
13:45
better than they used in the past过去. Now, this is, more or less,
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都比过去合理的多
13:50
if you look at the average平均 data数据 of the countries国家 -- they are like this.
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这里大家看到各国的数据 基本上都是平均数
13:57
Now that's dangerous危险, to use average平均 data数据, because there is such这样 a lot
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但是用平均数可能会很危险 因为国家内部也存在很大的差异
14:02
of difference区别 within countries国家. So if I go and look here, we can see
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我们看这里
14:08
that Uganda乌干达 today今天 is where South Korea韩国 was 1960. If I split分裂 Uganda乌干达,
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今天的乌干达和1960年的韩国差不多
14:14
there's quite相当 a difference区别 within Uganda乌干达. These are the quintiles昆泰 of Uganda乌干达.
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如果把乌干达分解开 可以看到内部的明显差异
14:19
The richest首富 20 percent百分 of Ugandans乌干达 are there.
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乌干达最富有的20%在右边
14:22
The poorest最穷 are down there. If I split分裂 South Africa非洲, it's like this.
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最贫穷的在左下边 如果把南非分解开
14:26
And if I go down and look at Niger尼日尔, where there was such这样 a terrible可怕 famine饥荒,
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尼日在下边 他们刚遭受一场恐怖的饥荒
14:31
lastly最后, it's like this. The 20 percent百分 poorest最穷 of Niger尼日尔 is out here,
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最贫穷的20%的尼日人在最左边
14:36
and the 20 percent百分 richest首富 of South Africa非洲 is there,
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而最富有的20%的南非人在最右边
14:39
and yet然而 we tend趋向 to discuss讨论 on what solutions解决方案 there should be in Africa非洲.
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今天我们仍然在讨论 什么方案能解决非洲的问题
14:44
Everything in this world世界 exists存在 in Africa非洲. And you can't
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世界上所有的问题非洲都有
14:47
discuss讨论 universal普遍 access访问 to HIVHIV [medicine医学] for that quintile五分之一 up here
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我们不可能讨论出一套通用方案 既能解决这些地方的艾滋病问题
14:51
with the same相同 strategy战略 as down here. The improvement起色 of the world世界
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同时也适用于这些地方
14:55
must必须 be highly高度 contextualized情境, and it's not relevant相应 to have it
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世界的发展一定要因地制宜来分析
15:00
on regional区域性 level水平. We must必须 be much more detailed详细.
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仅从各大洲的水平上来分析是不够的
15:03
We find that students学生们 get very excited兴奋 when they can use this.
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当学生们接触到这个软件的时候 他们都非常兴奋
15:07
And even more policy政策 makers制造商 and the corporate企业 sectors行业 would like to see
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此外,政策制定者,各企业部门 都会想知道世界的变化
15:12
how the world世界 is changing改变. Now, why doesn't this take place地点?
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但为什么大家仍然不知道(世界的变化)
15:16
Why are we not using运用 the data数据 we have? We have data数据 in the United联合的 Nations国家,
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为什么我们无法使用已知的数据呢
15:20
in the national国民 statistical统计 agencies机构
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我们的联合国,国家统计部门
15:22
and in universities高校 and other non-governmental民间 organizations组织.
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学院还有非政府组织都拥有数据
15:26
Because the data数据 is hidden down in the databases数据库.
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但数据被隐藏在底层的数据库里
15:28
And the public上市 is there, and the Internet互联网 is there, but we have still not used it effectively有效.
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而公众在上面(太阳)互联网在这里(地平线)并未得到有效的使用
15:33
All that information信息 we saw changing改变 in the world世界
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之前我们看到的 关于世界变化的信息
15:36
does not include包括 publicly-funded政府资助 statistics统计. There are some web卷筒纸 pages网页
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并不包括公众资助的统计数据
15:40
like this, you know, but they take some nourishment营养 down from the databases数据库,
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的确有一些网站依靠数据库的营养而存在着
15:46
but people put prices价格 on them, stupid passwords密码 and boring无聊 statistics统计.
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但这是要收费的 还有愚蠢的密码和讨厌的统计表格
15:51
(Laughter笑声) (Applause掌声)
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(笑声,掌声)
15:54
And this won't惯于 work. So what is needed需要? We have the databases数据库.
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这个是行不通的 我们需要什么?
15:58
It's not the new database数据库 you need. We have wonderful精彩 design设计 tools工具,
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数据库是现成的 不需要新的数据库
16:02
and more and more are added添加 up here. So we started开始
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我们有很好的视觉软件 还将有更多的问世
16:05
a nonprofit非营利性 venture冒险 which哪一个 we called -- linking链接 data数据 to design设计 --
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于是我们成立了一个非营利机构
16:10
we call it GapminderGapminder, from the London伦敦 underground地下, where they warn警告 you,
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我们称之为“数据与图样的联结” - Gapminder
16:13
"mind心神 the gap间隙." So we thought GapminderGapminder was appropriate适当.
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灵感来自伦敦地铁(他们提醒乘客“小心列车与站台间的缝隙”)
16:16
And we started开始 to write software软件 which哪一个 could link链接 the data数据 like this.
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而且我们制作了一个软件 把数据和图样联结起来
16:20
And it wasn't that difficult. It took some person years年份, and we have produced生成 animations动画.
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这个并不难 需要几个人花几年时间
16:26
You can take a data数据 set and put it there.
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建立数据库后大家就能看到动画
16:28
We are liberating解放 U.N. data数据, some few少数 U.N. organization组织.
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我们正尝试解放联合国的数据库
16:33
Some countries国家 accept接受 that their databases数据库 can go out on the world世界,
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少数联合国机构和几个国家已经开放了数据库
16:37
but what we really need is, of course课程, a search搜索 function功能.
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但我们最需要的是数据搜索引擎
16:40
A search搜索 function功能 where we can copy复制 the data数据 up to a searchable搜索 format格式
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依靠搜索引擎 我们先把原始数据复制成可搜索的格式
16:45
and get it out in the world世界. And what do we hear when we go around?
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再把数据发布到全世界 外界对这个设想的反应如何呢?
16:48
I've doneDONE anthropology人类学 on the main主要 statistical统计 units单位. Everyone大家 says,
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我尝试跟几个大型统计机构交涉
16:53
"It's impossible不可能. This can't be doneDONE. Our information信息 is so peculiar奇特
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所有人都说这是不可能的 “这行不通,我们的信息很独特,
16:57
in detail详情, so that cannot不能 be searched搜索 as others其他 can be searched搜索.
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不可能像其它数据那样检索的出来
17:00
We cannot不能 give the data数据 free自由 to the students学生们, free自由 to the entrepreneurs企业家 of the world世界."
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我们也不能免费把数据开放 给全世界的学生们和企业部门使用。”
17:05
But this is what we would like to see, isn't it?
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但这正是我们期望看到的,不是吗?
17:08
The publicly-funded政府资助 data数据 is down here.
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下边是公众资助采集的数据
17:11
And we would like flowers花卉 to grow增长 out on the Net.
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我们希望互联网上长出美丽的花朵
17:14
And one of the crucial关键 points is to make them searchable搜索, and then people can use
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关键的一步 是让这些数据可被搜索到
17:19
the different不同 design设计 tool工具 to animate活跃 it there.
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并借助软件实现动画的演示
17:21
And I have a pretty漂亮 good news新闻 for you. I have a good news新闻 that the present当下,
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我有个很好的消息要告诉大家
17:26
new Head of U.N. Statistics统计, he doesn't say it's impossible不可能.
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新上任的联合国统计部门的领导 并没有说这是不可能的
17:30
He only says, "We can't do it."
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他只说“我们不能这么做。”
17:32
(Laughter笑声)
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(笑声)
17:36
And that's a quite相当 clever聪明 guy, huh?
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他很聪明吧
17:38
(Laughter笑声)
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(笑声)
17:40
So we can see a lot happening事件 in data数据 in the coming未来 years年份.
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未来几年中 我们将会看到数据库的变化
17:44
We will be able能够 to look at income收入 distributions分布 in completely全然 new ways方法.
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我们会用全新的视角 来看收入的分配
17:48
This is the income收入 distribution分配 of China中国, 1970.
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这是1970年中国的收入分配
17:54
the income收入 distribution分配 of the United联合的 States状态, 1970.
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这是1970年美国的收入分配
17:59
Almost几乎 no overlap交叠. Almost几乎 no overlap交叠. And what has happened发生?
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几乎没有重叠 后来呢?
18:03
What has happened发生 is this: that China中国 is growing生长, it's not so equal等于 any longer,
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中国在增长,再也不像以前那样平等了
18:08
and it's appearing出现 here, overlooking俯瞰 the United联合的 States状态.
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它出现在右边,俯视着美国
18:12
Almost几乎 like a ghost, isn't it, huh?
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是不是像个鬼一样
18:14
(Laughter笑声)
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(笑声)
18:16
It's pretty漂亮 scary害怕. But I think it's very important重要 to have all this information信息.
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很吓人吧 我认为这些信息很重要
18:26
We need really to see it. And instead代替 of looking at this,
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大家很有必要看到这些
18:32
I would like to end结束 up by showing展示 the Internet互联网 users用户 per 1,000.
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另外我最后要给大家展示 每千人中的网民数量
18:37
In this software软件, we access访问 about 500 variables变量 from all the countries国家 quite相当 easily容易.
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这个软件能让我们很容易的看到 全球各国的近500个参数
18:42
It takes some time to change更改 for this,
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通过点击坐标轴
18:46
but on the axises轴系, you can quite相当 easily容易 get any variable变量 you would like to have.
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你能轻易改变参数的设定
18:51
And the thing would be to get up the databases数据库 free自由,
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我们的初衷是 数据免费下载且易于查找
18:56
to get them searchable搜索, and with a second第二 click点击, to get them
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然后再点一下鼠标 数据就成为图表的形式
18:59
into the graphic图像 formats格式, where you can instantly即刻 understand理解 them.
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那样大家就可以 立刻看明白这些数据了
19:04
Now, statisticians统计学家 doesn't like it, because they say that this
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统计学家们不喜欢这样子
19:07
will not show显示 the reality现实; we have to have statistical统计, analytical分析 methods方法.
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他们认为这不能准确地反映事实 传统的统计和分析方法是不能取代的
19:16
But this is hypothesis-generating假设生成.
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但数据动画可以帮助提出假说
19:19
I end结束 now with the world世界. There, the Internet互联网 is coming未来.
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最后我们看一下当今的互联网世界
19:23
The number of Internet互联网 users用户 are going up like this. This is the GDPGDP per capita人头.
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网民数量不断向上攀升(X轴是)人均国民生产总值
19:27
And it's a new technology技术 coming未来 in, but then amazingly令人惊讶, how well
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互联网是一项新技术 但令人惊讶的是
19:32
it fits适合 to the economy经济 of the countries国家. That's why the 100 dollar美元
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它的普及和国家的经济水平极其一致
19:37
computer电脑 will be so important重要. But it's a nice不错 tendency趋势.
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这也解释了100美元电脑的重要性 但这是很好的趋势
19:40
It's as if the world世界 is flattening扁平化 off, isn't it? These countries国家
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世界各国的差距将会缩小,不是吗
19:43
are lifting吊装 more than the economy经济 and will be very interesting有趣
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这些国家的互联网普及速度 超过了经济的发展速度
19:46
to follow跟随 this over the year, as I would like you to be able能够 to do
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我也希望大家都可以 自由使用公众资助采集的数据
19:50
with all the publicly公然 funded资助 data数据. Thank you very much.
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非常感谢!
19:53
(Applause掌声)
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(掌声)
Reviewed by Jenny Yang

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ABOUT THE SPEAKER
Hans Rosling - Global health expert; data visionary
In Hans Rosling’s hands, data sings. Global trends in health and economics come to vivid life. And the big picture of global development—with some surprisingly good news—snaps into sharp focus.

Why you should listen

Even the most worldly and well-traveled among us have had their perspectives shifted by Hans Rosling. A professor of global health at Sweden's Karolinska Institute, his work focused on dispelling common myths about the so-called developing world, which (as he pointed out) is no longer worlds away from the West. In fact, most of the Third World is on the same trajectory toward health and prosperity, and many countries are moving twice as fast as the west did.

What set Rosling apart wasn't just his apt observations of broad social and economic trends, but the stunning way he presented them. Guaranteed: You've never seen data presented like this. A presentation that tracks global health and poverty trends should be, in a word: boring. But in Rosling's hands, data sings. Trends come to life. And the big picture — usually hazy at best — snaps into sharp focus.

Rosling's presentations were grounded in solid statistics (often drawn from United Nations and World Bank data), illustrated by the visualization software he developed. The animations transform development statistics into moving bubbles and flowing curves that make global trends clear, intuitive and even playful. During his legendary presentations, Rosling took this one step farther, narrating the animations with a sportscaster's flair.

Rosling developed the breakthrough software behind his visualizations through his nonprofit Gapminder, founded with his son and daughter-in-law. The free software — which can be loaded with any data — was purchased by Google in March 2007. (Rosling met the Google founders at TED.)

Rosling began his wide-ranging career as a physician, spending many years in rural Africa tracking a rare paralytic disease (which he named konzo) and discovering its cause: hunger and badly processed cassava. He co-founded Médecins sans Frontièrs (Doctors without Borders) Sweden, wrote a textbook on global health, and as a professor at the Karolinska Institut in Stockholm initiated key international research collaborations. He's also personally argued with many heads of state, including Fidel Castro.

Hans Rosling passed away in February 2017. He is greatly missed.


More profile about the speaker
Hans Rosling | Speaker | TED.com