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

Hans Rosling用前所未有的方法詮釋數字統計

Filmed:
14,386,844 views

你肯定沒有看過這樣的數據演示。如解說體育比賽實況一般的生動與緊張,統計大師Hans Rosling將顛覆“發展中國家”這一理念。
- 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任務 to teach global全球 development發展
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大約10年前,我開始
00:29
to Swedish瑞典 undergraduate大學本科 students學生們. That was after having spent花費
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給瑞典大學生講授全球發展
00:33
about 20 years年份 together一起 with African非洲人 institutions機構 studying研究 hunger飢餓 in Africa非洲,
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之前的20年我一直在非洲研究飢餓問題
00:37
so I was sort分類 of expected預期 to know a little about the world世界.
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所以大家以為我對世界有些了解
00:41
And I started開始 in our medical university大學, Karolinska卡羅林斯卡 Institute研究所,
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在我們的Karolinska醫學院
00:46
an undergraduate大學本科 course課程 called Global全球 Health健康. But when you get
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我開設了一門本科生課程“全球健康”
00:50
that opportunity機會, you get a little nervous緊張. I thought, these students學生們
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剛開課的時候我還有些緊張
00:53
coming未來 to us actually其實 have the highest最高 grade年級 you can get
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因為來聽課的都是瑞典大學的優等生
00:56
in Swedish瑞典 college學院 systems系統 -- so, I thought, maybe they know everything
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他們或許早已了解我準備教的內容
00:59
I'm going to teach them about. So I did a pre-test預測試 when they came來了.
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於是在第一堂課裡,我作了一個小測試
01:03
And one of the questions問題 from which哪一個 I learned學到了 a lot was this one:
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其中有一道題讓我受益匪淺
01:06
"Which哪一個 country國家 has the highest最高 child兒童 mortality死亡 of these five pairs?"
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下列5對國家中,哪一個的兒童死亡率高於另一個?
01:10
And I put them together一起, so that in each pair of country國家,
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我所選擇的配對國家都是
01:14
one has twice兩次 the child兒童 mortality死亡 of the other. And this means手段 that
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一個的兒童死亡率是另一個的兩倍
01:19
it's much bigger a difference區別 than the uncertainty不確定 of the data數據.
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數據本身的不確定性可以忽略不計
01:24
I won't慣於 put you at a test測試 here, but it's Turkey火雞,
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今天我不會拿這來考大家
01:26
which哪一個 is highest最高 there, Poland波蘭, Russia俄國, Pakistan巴基斯坦 and South Africa非洲.
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土耳其,波蘭,俄羅斯,巴基斯坦和南非
01:31
And these were the results結果 of the Swedish瑞典 students學生們. I did it so I got
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這是瑞典學生的測驗結果
01:34
the confidence置信度 interval間隔, which哪一個 is pretty漂亮 narrow狹窄, and I got happy快樂,
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讓我高興的是
01:37
of course課程: a 1.8 right answer回答 out of five possible可能. That means手段 that
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5道題平均答對的只有1.8題
01:41
there was a place地點 for a professor教授 of international國際 health健康 --
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我這個教授還有這門課
01:44
(Laughter笑聲) and for my course課程.
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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編譯 the report報告
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但後來有天深夜,當我寫總結報告的時候
01:50
I really realized實現 my discovery發現. I have shown顯示
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我突然有了新的發現
01:54
that Swedish瑞典 top最佳 students學生們 know statistically統計學 significantly顯著 less
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瑞典大學的優等生們對世界的了解
01:59
about the world世界 than the chimpanzees黑猩猩.
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竟然還不如黑猩猩
02:01
(Laughter笑聲)
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(笑聲)
02:03
Because the chimpanzee黑猩猩 would score得分了 half right if I gave them
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因為黑猩猩們至少能蒙對一半
02:07
two bananas香蕉 with Sri斯里蘭卡 Lanka斯里蘭卡 and Turkey火雞. They would be right half of the cases.
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在兩個選項旁邊各放一根香蕉,就有一半的機率答對。
02:10
But the students學生們 are not there. The problem問題 for me was not ignorance無知;
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這些優等生們卻做不到。這不是由於知識缺乏
02:14
it was preconceived先入為主 ideas思路.
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而是他們先入為主的錯誤理念
02:17
I did also an unethical不道德的 study研究 of the professors教授 of the Karolinska卡羅林斯卡 Institute研究所
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我還把這個測試拿去給卡羅林斯卡學院的教授們做
02:21
(Laughter笑聲)
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(笑聲)
02:22
-- that hands out the Nobel諾貝爾 Prize in Medicine醫學,
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他們每年負責頒發諾貝爾醫學獎
02:24
and they are on par平價 with the chimpanzee黑猩猩 there.
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結果教授們和黑猩猩半斤八兩
02:26
(Laughter笑聲)
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(笑聲)
02:29
This is where I realized實現 that there was really a need to communicate通信,
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我意識到很有必要交流一下這個問題
02:33
because the data數據 of what's happening事件 in the world世界
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因為多數人並不知道
02:36
and the child兒童 health健康 of every一切 country國家 is very well aware知道的.
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世界各國的兒童健康的改善
02:39
We did this software軟件 which哪一個 displays顯示器 it like this: every一切 bubble泡沫 here is a country國家.
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我們作了一個軟件,每一個小球代表一個國家
02:44
This country國家 over here is China中國. This is India印度.
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這個是中國,這個是印度
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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小球的尺寸代表該國的人口,X軸是生育率
02:56
Because my students學生們, what they said
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我曾問過學生們
02:59
when they looked看著 upon the world世界, and I asked them,
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如果讓你們來審視這個世界
03:01
"What do you really think about the world世界?"
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你們的真實想法是什麼
03:03
Well, I first discovered發現 that the textbook教科書 was Tintin丁丁, mainly主要.
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其實這些教科書上都是丁丁歷險記(帶有殖民主義思想的漫畫)的人物
03:07
(Laughter笑聲)
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(笑聲)
03:08
And they said, "The world世界 is still 'we''我們' and 'them'他們.'
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學生們回答 世界是由“我們和他們”組成的
03:11
And we is Western西 world世界 and them is Third第三 World世界."
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“我們”指西方世界 “他們”指第三世界
03:14
"And what do you mean with Western西 world世界?" I said.
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我又問“什麼是西方世界?”
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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“西方世界壽命長且家庭小;第三世界壽命短而家庭大。”
03:22
So this is what I could display顯示 here. I put fertility生育能力 rate here: number of children孩子 per woman女人:
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那麼一起來看。X軸是生育率,每個婦女的育兒數
03:28
one, two, three, four, up to about eight children孩子 per woman女人.
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從每人1,2,3,4胎,到8胎
03:32
We have very good data數據 since以來 1962 -- 1960 about -- on the size尺寸 of families家庭 in all countries國家.
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我們有1962年之後的各國家庭大小的可靠數據
03:38
The error錯誤 margin餘量 is narrow狹窄. Here I put life expectancy期待 at birth分娩,
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數據誤差相當小。 Y軸是平均壽命
03:41
from 30 years年份 in some countries國家 up to about 70 years年份.
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從30歲到70歲不等
03:45
And 1962, there was really a group of countries國家 here
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1962年的時候的確有一群國家在上面
03:48
that was industrialized工業化 countries國家, and they had small families家庭 and long lives生活.
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這些是發達國家,他們家庭小,壽命長
03:53
And these were the developing發展 countries國家:
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而這些則是發展中國家
03:55
they had large families家庭 and they had relatively相對 short lives生活.
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他們家庭大,壽命也相對短些
03:58
Now what has happened發生 since以來 1962? We want to see the change更改.
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從1962年到今天 世界有什麼變化嗎?
04:02
Are the students學生們 right? Is it still two types類型 of countries國家?
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學生們正確嗎?國家還是分為2類嗎?
04:06
Or have these developing發展 countries國家 got smaller families家庭 and they live生活 here?
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或者發展中國家的家庭變小 (這些小球)移動到了左邊?
04:09
Or have they got longer lives生活 and live生活 up there?
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或者發展中國家人們的壽命變長 (這些小球)移動到了上面?
04:11
Let's see. We stopped停止 the world世界 then. This is all U.N. statistics統計
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我們一起看看,這些數據都來自於聯合國
04:14
that have been available可得到. Here we go. Can you see there?
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大家看到沒有?
04:17
It's China中國 there, moving移動 against反對 better health健康 there, improving提高 there.
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這個是中國,他們在往上移動,健康狀況不斷改善
04:20
All the green綠色 Latin拉丁 American美國 countries國家 are moving移動 towards smaller families家庭.
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這些綠色的拉丁美洲國家 正朝向小家庭的方向移動
04:23
Your yellow黃色 ones那些 here are the Arabic阿拉伯 countries國家,
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這些黃色的小球是阿拉伯國家
04:26
and they get larger families家庭, but they -- no, longer life, but not larger families家庭.
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壽命在變長但家庭規模不變
04:30
The Africans非洲人 are the green綠色 down here. They still remain here.
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非洲國家是下面的綠球,他們一直在下面
04:33
This is India印度. Indonesia's印尼 moving移動 on pretty漂亮 fast快速.
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這個是印度,印度尼西亞的移動速度非常快
04:36
(Laughter笑聲)
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(笑聲)
04:37
And in the '80s here, you have Bangladesh孟加拉國 still among其中 the African非洲人 countries國家 there.
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80年代的時候,孟加拉國仍然和非洲國家在一起
04:40
But now, Bangladesh孟加拉國 -- it's a miracle奇蹟 that happens發生 in the '80s:
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但是80年代的奇蹟發生在孟加拉國
04:43
the imams伊瑪目 start開始 to promote促進 family家庭 planning規劃.
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媽媽們開始宣傳和普及計劃生育
04:46
They move移動 up into that corner. And in '90s, we have the terrible可怕 HIVHIV epidemic疫情
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他們向左上角移動。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國家
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導致非洲國家的平均壽命縮短
04:54
and all the rest休息 of them move移動 up into the corner,
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而其他國家都向左上角移動
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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大家都有了長壽命和小家庭,而世界也煥然一新了
05:02
(Applause掌聲)
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(掌聲)
05:15
Let me make a comparison對照 directly between之間 the United聯合的 States狀態 of America美國 and Vietnam越南.
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現在我們對比一下美國和越南
05:20
1964: America美國 had small families家庭 and long life;
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1964年的美國家庭小壽命長
05:25
Vietnam越南 had large families家庭 and short lives生活. And this is what happens發生:
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越南的家庭大而壽命短。這是後來的變化
05:29
the data數據 during the war戰爭 indicate表明 that even with all the death死亡,
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越戰時期的數據顯示,儘管戰爭造成傷亡
05:35
there was an improvement起色 of life expectancy期待. By the end結束 of the year,
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越南人的平均壽命仍有提高
05:38
the family家庭 planning規劃 started開始 in Vietnam越南 and they went for smaller families家庭.
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70年代末期,越南的計劃生育減小了家庭規模
05:41
And the United聯合的 States狀態 up there is getting得到 for longer life,
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美國人的平均壽命也在延長
05:44
keeping保持 family家庭 size尺寸. And in the '80s now,
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而家庭規模不變
05:47
they give up communist共產 planning規劃 and they go for market市場 economy經濟,
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到了90年代,越南由計劃經濟轉為市場經濟
05:50
and it moves移動 faster更快 even than social社會 life. And today今天, we have
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其經濟發展的速度超過了社會的發展
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)越南人的平均壽命和家庭規模
05:59
here in Vietnam越南, 2003, as in United聯合的 States狀態, 1974, by the end結束 of the war戰爭.
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已經和越戰結束時(1974)的美國一樣
06:06
I think we all -- if we don't look in the data數據 --
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如果沒有看到這些數據的話
06:10
we underestimate低估 the tremendous巨大 change更改 in Asia亞洲, which哪一個 was
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我們會低估了亞洲的巨大變化
06:14
in social社會 change更改 before we saw the economical經濟 change更改.
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這些超前於經濟發展的社會變革
06:18
Let's move移動 over to another另一個 way here in which哪一個 we could display顯示
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下面我們換個視角
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軸顯示了全世界的收入分佈
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間隙 between之間 rich豐富 and poor較差的 any longer. This is a myth神話.
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富與窮之間的鴻溝幾乎消失了,簡直是個奇蹟
06:39
There's a little hump駝峰 here. But there are people all the way.
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這裡還有一個很小的峰,但總體上是均數分佈的
06:44
And if we look where the income收入 ends結束 up -- the income收入 --
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我們看看收入的分配情況
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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這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最窮 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節目 that the concept概念
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最貧窮的20%那部分人只得到2%
07:06
of developing發展 countries國家 is extremely非常 doubtful. We think about aid援助, like
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可見發展中國家的理念極其的不確切
07:10
these people here giving aid援助 to these people here. But in the middle中間,
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我們總以為最富的人應該給最窮的人提供援助
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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其實中間這部分才是世界人口的主體,而他們僅得到全部收入的24%
07:19
We heard聽說 it in other forms形式. And who are these?
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這是個老問題了,中間這些人是誰?
07:23
Where are the different不同 countries國家? I can show顯示 you Africa非洲.
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他們在哪些國家?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貧窮.
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非洲佔世界人口的十分之一,多數是窮人
07:32
This is OECD經合組織. The rich豐富 country國家. The country國家 club俱樂部 of the U.N.
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這個代表富裕的經合組織成員國,聯合國俱樂部的會員
07:37
And they are over here on this side. Quite相當 an overlap交疊 between之間 Africa非洲 and OECD經合組織.
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他們在這邊,很小一部分與非洲重疊
07:42
And this is Latin拉丁 America美國. It has everything on this Earth地球,
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這是拉丁美洲,他們可以代表全世界
07:45
from the poorest最窮 to the richest首富, in Latin拉丁 America美國.
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從最貧窮到最富有的人都在那裡
07:48
And on top最佳 of that, we can put East Europe歐洲, we can put East Asia亞洲,
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再往上是東歐,東亞還有南亞
07:53
and we put South Asia亞洲. And how did it look like if we go back in time,
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過去是什麼樣子的呢?
07:58
to about 1970? Then there was more of a hump駝峰.
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如果我們回到1970年,這裡有一個明顯的峰
08:03
And we have most who lived生活 in absolute絕對 poverty貧窮 were Asians亞洲人.
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這些絕對貧困的人大多數在亞洲
08:07
The problem問題 in the world世界 was the poverty貧窮 in Asia亞洲. And if I now let the world世界 move移動 forward前鋒,
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那時世界的問題就在於亞洲的貧窮
08:14
you will see that while population人口 increase增加, there are
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後來隨著人口的增長
08:17
hundreds數以百計 of millions百萬 in Asia亞洲 getting得到 out of poverty貧窮 and some others其他
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數以億計的亞洲人擺脫了貧困
08:20
getting得到 into poverty貧窮, and this is the pattern模式 we have today今天.
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另外一些人卻陷入貧窮,這就是今天的世界
08:23
And the best最好 projection投影 from the World世界 Bank銀行 is that this will happen發生,
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而這是世界銀行對未來最樂觀的預測
08:27
and we will not have a divided分為 world世界. We'll have most people in the middle中間.
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世界再也不是貧富懸殊的,大多數人擁有中等的收入
08:31
Of course課程 it's a logarithmic對數的 scale規模 here,
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當然這是指數冪分佈的圖
08:33
but our concept概念 of economy經濟 is growth發展 with percent百分. We look upon it
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因為經濟的增長是用百分比來衡量的
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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我們用百分比的變化來評估經濟增長
08:44
GDPGDP per capita人頭 instead代替 of family家庭 income收入, and I turn these
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下面把X軸改為人均國內生產總值
08:48
individual個人 data數據 into regional區域性 data數據 of gross domestic國內 product產品,
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個人的數據轉為各大洲的數據
08:54
and I take the regions地區 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經合組織 there, and you have sub-Saharan撒哈拉以南 Africa非洲 there,
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這個是經合組織國家,這是撒哈拉以南非洲
09:01
and we take off the Arab阿拉伯 states狀態 there,
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我們把阿拉伯國家
09:04
coming未來 both from Africa非洲 and from Asia亞洲, and we put them separately分別,
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從非洲和亞洲單獨分出來
09:08
and we can expand擴大 this axis, and I can give it a new dimension尺寸 here,
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然後把X軸延伸一下,再加上一個新的維度
09:13
by adding加入 the social社會 values there, child兒童 survival生存.
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一個有社會價值的參數:兒童生存率
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軸代表經濟,Y軸顯示兒童存活的比率
09:21
In some countries國家, 99.7 percent百分 of children孩子 survive生存 to five years年份 of age年齡;
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一些國家的99.7%的小孩可以活到5歲以上
09:25
others其他, only 70. And here it seems似乎 there is a gap間隙
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另一些國家只有70%。很明顯可以看到
09:29
between之間 OECD經合組織, Latin拉丁 America美國, East Europe歐洲, East Asia亞洲,
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經合組織成員國和拉丁美洲,東歐,東亞
09:33
Arab阿拉伯 states狀態, South Asia亞洲 and sub-Saharan撒哈拉以南 Africa非洲.
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阿拉伯國家,南亞和非洲撒哈拉以南地區
09:37
The linearity線性 is very strong強大 between之間 child兒童 survival生存 and money.
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兒童生存率和經濟之間聯繫非常緊密
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區分解成各個國家
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國家.
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分佈靠上邊的國家擁有更高的健康水平
09:55
And when it burst爆裂, the size尺寸 of its country國家 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國是如此分佈的,球的尺寸代表該國人口
10:00
Sierra內華達 Leone塞拉利昂 down there. Mauritius毛里求斯 is up there. Mauritius毛里求斯 was the first country國家
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塞拉里昂在下邊,毛里求斯在上邊
10:04
to get away with trade貿易 barriers障礙, and they could sell their sugar --
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毛里求斯是第一個消除了貿易壁壘的國家
10:08
they could sell their textiles紡織品 -- on equal等於 terms條款 as the people in Europe歐洲 and North America美國.
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他們的蔗糖和紡織品的貿易協定與歐洲和北美一樣
10:13
There's a huge巨大 difference區別 between之間 Africa非洲. And Ghana加納 is here in the middle中間.
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但是非洲內部的差異非常巨大。加納在中部
10:17
In Sierra內華達 Leone塞拉利昂, humanitarian人道主義 aid援助.
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塞拉里昂需要人道主義援助
10:20
Here in Uganda烏干達, development發展 aid援助. Here, time to invest投資; there,
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烏干達則需要發展援助,在加納可以進行投資了
10:25
you can go for a holiday假日. It's a tremendous巨大 variation變異
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毛里求斯則可以去度假。非洲內部的差異之大確實很驚人
10:28
within Africa非洲 which哪一個 we rarely很少 often經常 make -- that it's equal等於 everything.
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而我們卻總以為非洲國家都差不多
10:33
I can split分裂 South Asia亞洲 here. India's印度 the big bubble泡沫 in the middle中間.
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下面分解南亞各國,印度是中間的藍色大球
10:37
But a huge巨大 difference區別 between之間 Afghanistan阿富汗 and Sri斯里蘭卡 Lanka斯里蘭卡.
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而斯里蘭卡和阿富汗有著巨大差異
10:41
I can split分裂 Arab阿拉伯 states狀態. How are they? Same相同 climate氣候, same相同 culture文化,
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把阿拉伯世界分解來看,儘管是相同的氣候,相同的文化
10:45
same相同 religion宗教 -- huge巨大 difference區別. Even between之間 neighbors鄰居.
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相同的宗教,卻有巨大的差異
10:49
Yemen也門, civil國內 war戰爭. United聯合的 Arab阿拉伯 Emirate酋長國, money which哪一個 was quite相當 equally一樣 and well used.
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也門在打內戰,鄰國阿聯酋卻躺在錢堆裡
10:54
Not as the myth神話 is. And that includes包括 all the children孩子 of the foreign國外 workers工人 who are in the country國家.
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而且(阿聯酋的)兒童健康數據包含了所有的外籍勞工
11:01
Data數據 is often經常 better than you think. Many許多 people say data數據 is bad.
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大家總說數據不准確數據,其實比我們想像的好很多
11:06
There is an uncertainty不確定 margin餘量, but we can see the difference區別 here:
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數據是有誤差
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遠大於數據的誤差
11:11
than the weakness弱點 of the data數據. East Europe歐洲:
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再看東歐
11:14
Soviet蘇聯 economy經濟 for a long time, but they come out after 10 years年份
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在蘇聯經濟模式下發展了多年,但在過去10年
11:20
very, very differently不同. And there is Latin拉丁 America美國.
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卻經歷了巨大的變化
11:23
Today今天, we don't have to go to Cuba古巴 to find a healthy健康 country國家 in Latin拉丁 America美國.
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當今的拉丁美洲,古巴再也不是唯一的健康國家了
11:27
Chile智利 will have a lower降低 child兒童 mortality死亡 than Cuba古巴 within some few少數 years年份 from now.
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幾年後,智利的兒童死亡率將低於古巴
11:32
And here we have high-income高收入 countries國家 in the OECD經合組織.
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這些是經合組織成員國
11:35
And we get the whole整個 pattern模式 here of the world世界,
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這裡顯示的就是我們的世界
11:39
which哪一個 is more or less like this. And if we look at it,
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大概就是這樣的情形。如果我們回到過去
11:44
how it looks容貌 -- the world世界, in 1960, it starts啟動 to move移動. 1960.
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看看世界是怎樣的。從1960年開始
11:50
This is Mao Tse-tung謝彤. He brought health健康 to China中國. And then he died死亡.
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1960年(中國有)毛澤東,他給中國帶來了健康
11:53
And then Deng Xiaoping小平 came來了 and brought money to China中國, and brought them into the mainstream主流 again.
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他去世後鄧小平給中國帶來了金錢,同時把中國帶回到世界的主流當中
11:58
And we have seen看到 how countries國家 move移動 in different不同 directions方向 like this,
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其他國家的移動方向也不盡相同
12:02
so it's sort分類 of difficult to get
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很難找出哪個國家
12:06
an example country國家 which哪一個 shows節目 the pattern模式 of the world世界.
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能代表全世界的發展模式
12:11
But I would like to bring帶來 you back to about here at 1960.
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我們回到1960年做個比較
12:17
I would like to compare比較 South Korea韓國, which哪一個 is this one, with Brazil巴西,
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先選中韓國(左邊的小黃球);巴西(右邊的黃綠色大球)
12:27
which哪一個 is this one. The label標籤 went away for me here. And I would like to compare比較 Uganda烏干達,
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烏干達(Y軸上面的小紅球)
12:32
which哪一個 is there. And I can run it forward前鋒, like this.
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隨著時間的推移,我們看到
12:37
And you can see how South Korea韓國 is making製造 a very, very fast快速 advancement進步,
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韓國的發展速度非常非常快
12:46
whereas Brazil巴西 is much slower比較慢.
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巴西就慢得多
12:49
And if we move移動 back again, here, and we put on trails步道 on them, like this,
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我們再回到過去,給每個球畫出運動的軌跡
12:55
you can see again that the speed速度 of development發展
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可以看到,發展速度的差距非常大
12:59
is very, very different不同, and the countries國家 are moving移動 more or less
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雖然各國的經濟和健康發展的軌跡大同小異
13:05
in the same相同 rate as money and health健康, but it seems似乎 you can move移動
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但是健康水平起點較高的國家
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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發展速度遠超過經濟水平起點高的
13:14
And to show顯示 that, you can put on the way of United聯合的 Arab阿拉伯 Emirate酋長國.
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為了說明這一點,我們看看阿聯酋
13:18
They came來了 from here, a mineral礦物 country國家. They cached緩存 all the oil;
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他們從這裡出發,一個資源型國家
13:21
they got all the money; but health健康 cannot不能 be bought at the supermarket超級市場.
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他們靠石油大把賺錢,但健康絕不是超市裡的貨物
13:25
You have to invest投資 in health健康. You have to get kids孩子 into schooling教育.
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需要衛生方面的投資,需要提高兒童的教育水平
13:29
You have to train培養 health健康 staff員工. You have to educate教育 the population人口.
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需要培訓衛生工作者,還要教育民眾
13:32
And Sheikh謝赫 Sayed賽義德 did that in a fairly相當 good way.
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Sheikh Sayed 幹的非常漂亮
13:35
In spite儘管 of falling落下 oil prices價格, he brought this country國家 up here.
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儘管油價下跌了,他仍改善了阿聯酋的健康
13:39
So we've我們已經 got a much more mainstream主流 appearance出現 of the world世界,
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這裡我們可以看到世界發展的主流
13:43
where all countries國家 tend趨向 to use their money
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各國對資金的分配和使用
13:45
better than they used in the past過去. Now, this is, more or less,
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都比過去合理的多
13:50
if you look at the average平均 data數據 of the countries國家 -- they are like this.
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這里大家看到各國的數據基本上都是平均數
13:57
Now that's dangerous危險, to use average平均 data數據, because there is such這樣 a lot
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但是用平均數可能會很危險
因為國家內部也存在很大的差異
14:02
of difference區別 within countries國家. So if I go and look here, we can see
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我們看這裡
14:08
that Uganda烏干達 today今天 is where South Korea韓國 was 1960. If I split分裂 Uganda烏干達,
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今天的烏干達和1960年的韓國差不多
14:14
there's quite相當 a difference區別 within Uganda烏干達. These are the quintiles昆泰 of Uganda烏干達.
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如果把烏干達分解開,可以看到內部的明顯差異
14:19
The richest首富 20 percent百分 of Ugandans烏干達 are there.
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烏干達最富有的20%在右邊
14:22
The poorest最窮 are down there. If I split分裂 South Africa非洲, it's like this.
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最貧窮的在左下邊。如果把南非分解開
14:26
And if I go down and look at Niger尼日爾, where there was such這樣 a terrible可怕 famine飢荒,
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尼日在下邊,他們剛遭受一場恐怖的飢荒
14:31
lastly最後, it's like this. The 20 percent百分 poorest最窮 of Niger尼日爾 is out here,
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最貧窮的20%的尼日人在最左邊
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%的南非人在最右邊
14:39
and yet然而 we tend趨向 to discuss討論 on what solutions解決方案 there should be in Africa非洲.
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今天我們仍然在討論什麼方案能解決非洲的問題
14:44
Everything in this world世界 exists存在 in Africa非洲. And you can't
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世界上所有的問題非洲都有
14:47
discuss討論 universal普遍 access訪問 to HIVHIV [medicine醫學] for that quintile五分之一 up here
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我們不可能討論出一套通用方案,既能解決這些地方的艾滋病問題
14:51
with the same相同 strategy戰略 as down here. The improvement起色 of the world世界
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同時也適用於這些地方
14:55
must必須 be highly高度 contextualized情境, and it's not relevant相應 to have it
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世界的發展一定要因地制宜來分析
15:00
on regional區域性 level水平. We must必須 be much more detailed詳細.
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僅從各大洲的水平上來分析是不夠的
15:03
We find that students學生們 get very excited興奮 when they can use this.
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當學生們接觸到這個軟件的時候他們都非常興奮
15:07
And even more policy政策 makers製造商 and the corporate企業 sectors行業 would like to see
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此外,政策制定者,各企業部門都會想知道世界的變化
15:12
how the world世界 is changing改變. Now, why doesn't this take place地點?
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但為什麼大家仍然不知道(世界的變化)
15:16
Why are we not using運用 the data數據 we have? We have data數據 in the United聯合的 Nations國家,
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為什麼我們無法使用已知的數據呢
15:20
in the national國民 statistical統計 agencies機構
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我們的聯合國,國家統計部門
15:22
and in universities高校 and other non-governmental民間 organizations組織.
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學院還有非政府組織都擁有數據
15:26
Because the data數據 is hidden down in the databases數據庫.
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但數據被隱藏在底層的數據庫裡
15:28
And the public上市 is there, and the Internet互聯網 is there, but we have still not used it effectively有效.
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而公眾在上面(太陽),互聯網(地平線)並未得到有效的使用
15:33
All that information信息 we saw changing改變 in the world世界
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之前我們看到的關於世界變化的信息
15:36
does not include包括 publicly-funded政府資助 statistics統計. There are some web捲筒紙 pages網頁
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並不包括公眾資助的統計數據
15:40
like this, you know, but they take some nourishment營養 down from the databases數據庫,
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的確有一些網站依靠數據庫的營養而存在著
15:46
but people put prices價格 on them, stupid passwords密碼 and boring無聊 statistics統計.
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但這是要收費的,還有愚蠢的密碼和討厭的統計表格
15:51
(Laughter笑聲) (Applause掌聲)
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(笑聲,掌聲)
15:54
And this won't慣於 work. So what is needed需要? We have the databases數據庫.
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這個是行不通的。我們需要什麼?
15:58
It's not the new database數據庫 you need. We have wonderful精彩 design設計 tools工具,
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數據庫是現成的,不需要新的數據庫
16:02
and more and more are added添加 up here. So we started開始
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我們有很好的視覺軟件,還將有更多的問世
16:05
a nonprofit非營利性 venture冒險 which哪一個 we called -- linking鏈接 data數據 to design設計 --
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於是我們成立了一個非營利機構
16:10
we call it GapminderGapminder, from the London倫敦 underground地下, where they warn警告 you,
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我們稱之為“數據與圖樣的聯結” - Gapminder
16:13
"mind心神 the gap間隙." So we thought GapminderGapminder was appropriate適當.
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靈感來自倫敦地鐵(他們提醒乘客“小心列車與站台間的縫隙”)
16:16
And we started開始 to write software軟件 which哪一個 could link鏈接 the data數據 like this.
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而且我們製作了一個軟件,把數據和圖樣聯結起來
16:20
And it wasn't that difficult. It took some person years年份, and we have produced生成 animations動畫.
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這個並不難,需要幾個人花幾年時間
16:26
You can take a data數據 set and put it there.
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建立數據庫後大家就能看到動畫
16:28
We are liberating解放 U.N. data數據, some few少數 U.N. organization組織.
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我們正嘗試解放聯合國的數據庫
16:33
Some countries國家 accept接受 that their databases數據庫 can go out on the world世界,
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少數聯合國機構和幾個國家已經開放了數據庫
16:37
but what we really need is, of course課程, a search搜索 function功能.
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但我們最需要的是數據搜索引擎
16:40
A search搜索 function功能 where we can copy複製 the data數據 up to a searchable搜索 format格式
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依靠搜索引擎,我們先把原始數據複製成可搜索的格式
16:45
and get it out in the world世界. And what do we hear when we go around?
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再把數據發佈到全世界。外界對這個設想的反應如何呢?
16:48
I've doneDONE anthropology人類學 on the main主要 statistical統計 units單位. Everyone大家 says,
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我嘗試跟幾個大型統計機構交涉
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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所有人都說,這是不可能的,“這行不通,我們的信息很獨特,
16:57
in detail詳情, so that cannot不能 be searched搜索 as others其他 can be searched搜索.
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不可能像其它數據那樣檢索的出來
17:00
We cannot不能 give the data數據 free自由 to the students學生們, free自由 to the entrepreneurs企業家 of the world世界."
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我們也不能免費把數據開放,給全世界的學生們和企業部門使用。 ”
17:05
But this is what we would like to see, isn't it?
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但這正是我們期望看到的,不是嗎?
17:08
The publicly-funded政府資助 data數據 is down here.
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下邊是公眾資助採集的數據
17:11
And we would like flowers花卉 to grow增長 out on the Net.
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我們希望互聯網上長出美麗的花朵
17:14
And one of the crucial關鍵 points is to make them searchable搜索, and then people can use
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關鍵的一步,是讓這些數據可被搜索到
17:19
the different不同 design設計 tool工具 to animate活躍 it there.
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並藉助軟件實現動畫的演示
17:21
And I have a pretty漂亮 good news新聞 for you. I have a good news新聞 that the present當下,
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我有個很好的消息要告訴大家
17:26
new Head of U.N. Statistics統計, he doesn't say it's impossible不可能.
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新上任的聯合國統計部門的領導並沒有說這是不可能的
17:30
He only says, "We can't do it."
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他只說“我們不能這麼做。”
17:32
(Laughter笑聲)
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(笑聲)
17:36
And that's a quite相當 clever聰明 guy, huh?
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他很聰明吧
17:38
(Laughter笑聲)
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(笑聲)
17:40
So we can see a lot happening事件 in data數據 in the coming未來 years年份.
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未來幾年中我們將會看到數據庫的變化
17:44
We will be able能夠 to look at income收入 distributions分佈 in completely全然 new ways方法.
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我們會用全新的視角來看收入的分配
17:48
This is the income收入 distribution分配 of China中國, 1970.
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這是1970年中國的收入分配
17:54
the income收入 distribution分配 of the United聯合的 States狀態, 1970.
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這是1970年美國的收入分配
17:59
Almost幾乎 no overlap交疊. Almost幾乎 no overlap交疊. And what has happened發生?
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幾乎沒有重疊,後來呢?
18:03
What has happened發生 is this: that China中國 is growing生長, it's not so equal等於 any longer,
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中國在增長,再也不像以前那樣平等了
18:08
and it's appearing出現 here, overlooking俯瞰 the United聯合的 States狀態.
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它出現在右邊,俯視著美國
18:12
Almost幾乎 like a ghost, isn't it, huh?
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是不是像個鬼一樣
18:14
(Laughter笑聲)
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(笑聲)
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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很嚇人吧,我認為這些信息很重要
18:26
We need really to see it. And instead代替 of looking at this,
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大家很有必要看到這些
18:32
I would like to end結束 up by showing展示 the Internet互聯網 users用戶 per 1,000.
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另外我最後要給大家展示,每千人中的網民數量
18:37
In this software軟件, we access訪問 about 500 variables變量 from all the countries國家 quite相當 easily容易.
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這個軟件能讓我們很容易的看到全球各國的近500個參數
18:42
It takes some time to change更改 for this,
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通過點擊坐標軸
18:46
but on the axises軸系, you can quite相當 easily容易 get any variable變量 you would like to have.
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你能輕易改變參數的設定
18:51
And the thing would be to get up the databases數據庫 free自由,
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我們的初衷是,數據免費下載且易於查找
18:56
to get them searchable搜索, and with a second第二 click點擊, to get them
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然後再點一下鼠標,數據就成為圖表的形式
18:59
into the graphic圖像 formats格式, where you can instantly即刻 understand理解 them.
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那樣大家就可以立刻看明白這些數據了
19:04
Now, statisticians統計學家 doesn't like it, because they say that this
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統計學家們不喜歡這樣子
19:07
will not show顯示 the reality現實; we have to have statistical統計, analytical分析 methods方法.
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他們認為這不能準確地反映事實,傳統的統計和分析方法是不能取代的
19:16
But this is hypothesis-generating假設生成.
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但數據動畫可以幫助提出假說
19:19
I end結束 now with the world世界. There, the Internet互聯網 is coming未來.
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最後我們看一下當今的互聯網世界
19:23
The number of Internet互聯網 users用戶 are going up like this. This is the GDPGDP per capita人頭.
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網民數量不斷向上攀升,(X軸是)人均國民生產總值
19:27
And it's a new technology技術 coming未來 in, but then amazingly令人驚訝, how well
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互聯網是一項新技術,但令人驚訝的是
19:32
it fits適合 to the economy經濟 of the countries國家. That's why the 100 dollar美元
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它的普及和國家的經濟水平極其一致
19:37
computer電腦 will be so important重要. But it's a nice不錯 tendency趨勢.
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這也解釋了100美元電腦的重要性,但這是很好的趨勢
19:40
It's as if the world世界 is flattening扁平化 off, isn't it? These countries國家
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世界各國的差距將會縮小,不是嗎
19:43
are lifting吊裝 more than the economy經濟 and will be very interesting有趣
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這些國家的互聯網普及速度超過了經濟的發展速度
19:46
to follow跟隨 this over the year, as I would like you to be able能夠 to do
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我也希望大家都可以自由使用公眾資助採集的數據
19:50
with all the publicly公然 funded資助 data數據. Thank you very much.
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非常感謝!
19:53
(Applause掌聲)
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www.gapminder.org

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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