TED演講：貧窮？富有？讓數(shù)據(jù)來說話

　　About 10 years ago, I took on the task to teach global development to Swedish undergraduate students. That was after having spent about 20 years together with African institutions studying hunger in Africa, so I was sort of expected to know a little about the world. And I started in our medical university, Karolinska Institute, an undergraduate course called Global Health. But when you get that opportunity, you get a little nervous. I thought, these students coming to us actually have the highest grade you can get in Swedish college systems -- so, I thought, maybe they know everything I'm going to teach them about. So I did a pre-test when they came. And one of the questions from which I learned a lot was this one: "Which country has the highest child mortality of these five pairs?"

　　大約在十年前， 我擔當起 給瑞典大學生講授全球發(fā)展的任務 之前的20年我一直在非洲研究饑餓問題 所以大家以為我對世界有些了解 在我們的卡羅林斯卡醫(yī)學院 我開設了一門本科生課程“全球健康” 剛開課的時候我還有些緊張 因為來聽課的都是瑞典大學的優(yōu)等生 他們或許早已了解我準備教的內(nèi)容 于是在第一堂課里，我作了一個小測試 其中有一道題讓我受益匪淺 下列5對國家中，哪一個的兒童死亡率高于另一個?

　　And I put them together, so that in each pair of country, one has twice the child mortality of the other. And this means that it's much bigger a difference than the uncertainty of the data. I won't put you at a test here, but it's Turkey, which is highest there, Poland, Russia, Pakistan and South Africa. And these were the results of the Swedish students. I did it so I got the confidence interval, which is pretty narrow, and I got happy, of course: a 1.8 right answer out of five possible. That means that there was a place for a professor of international health -- (Laughter) and for my course.

　　我所選擇的配對國家都是 一個的兒童死亡率是另一個的兩倍,因為數(shù)據(jù)差距很大 因此數(shù)據(jù)本身的不確定性可以忽略不計 今天我不會拿這來考大家 土耳其，波蘭，俄羅斯，巴基斯坦和南非 這是瑞典學生的測驗結果 讓我高興的是 5題中平均答對的只有1.8題 我這個教授還有這門課 因此都有了存在的必要

　　But one late night, when I was compiling the report I really realized my discovery. I have shown that Swedish top students know statistically significantly less about the world than the chimpanzees. (Laughter) Because the chimpanzee would score half right if I gave them two bananas with Sri Lanka and Turkey. They would be right half of the cases.

　　但后來有天深夜，當我寫總結報告的時候 我突然有了新的發(fā)現(xiàn) 瑞典大學的優(yōu)等生們對世界的了解 竟然還不如黑猩猩 (笑聲) 因為黑猩猩們至少能蒙對一半 在兩個選項旁邊各放一根香蕉，就有一半的幾率答對。

　　But the students are not there. The problem for me was not ignorance; it was preconceived ideas.

　　這些優(yōu)等生們卻做不到。這不是由于知識缺乏 而是他們先入為主的錯誤理念

　　I did also an unethical study of the professors of the Karolinska Institute (Laughter) -- that hands out the Nobel Prize in Medicine, and they are on par with the chimpanzee there. (Laughter) This is where I realized that there was really a need to communicate, because the data of what's happening in the world and the child health of every country is very well aware.

　　我還把這個測試拿去 給卡羅林斯卡學院的教授們做 (笑聲) 他們每年負責頒發(fā)諾貝爾醫(yī)學獎 結果教授們和黑猩猩半斤八兩 (笑聲) 我意識到很有必要交流一下這個問題 因為多數(shù)人并不知道 世界各國的兒童健康的改善

　　We did this software which displays it like this: every bubble here is a country. This country over here is China. This is India. The size of the bubble is the population, and on this axis here I put fertility rate. Because my students, what they said when they looked upon the world, and I asked them, "What do you really think about the world?" Well, I first discovered that the textbook was Tintin, mainly. (Laughter) And they said, "The world is still 'we' and 'them.' And we is Western world and them is Third World." "And what do you mean with Western world?" I said. "Well, that's long life and small family, and Third World is short life and large family."

　　我們作了一個軟件，每一個小球代表一個國家 這個是中國，這個是印度 小球的尺寸代表該國的人口，X軸是生育率 我曾問過學生們 如果讓你們來審視這個世界 你們的真實想法是什么 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 (笑聲) 學生們回答 世界是由“我們和他們”組成的 “我們”指西方世界 “他們”指第三世界 我又問 “什么是西方世界?” “西方世界壽命長且家庭小; 第三世界壽命短而家庭大。”

　　So this is what I could display here. I put fertility rate here: number of children per woman: one, two, three, four, up to about eight children per woman. We have very good data since 1962 -- 1960 about -- on the size of families in all countries. The error margin is narrow. Here I put life expectancy at birth, from 30 years in some countries up to about 70 years. And 1962, there was really a group of countries here that was industrialized countries, and they had small families and long lives. And these were the developing countries: they had large families and they had relatively short lives. Now what has happened since 1962? We want to see the change. Are the students right? Is it still two types of countries? Or have these developing countries got smaller families and they live here? Or have they got longer lives and live up there?

　　那么一起來看看 X軸是生育率，每個婦女的育兒數(shù) 從每人1，2，3，4胎，到8胎 我們有1962年之后的各國家庭大小的可靠數(shù)據(jù) 數(shù)據(jù)誤差相當小。Y軸是平均壽命 從30歲到70歲不等 1962年的時候 的確有一群國家在上面 這些是發(fā)達國家，他們家庭小，壽命長 而這些則是發(fā)展中國家 他們家庭大，壽命也相對短些 從1962年到今天 世界有什么變化嗎? 我們來看看 學生們正確嗎?國家還是分為2類嗎? 或者發(fā)展中國家的家庭變小(這些小球)移動到了左邊? 或者發(fā)展中國家人們的壽命變長(這些小球)移動到了上面?

　　Let's see. We stopped the world then. This is all U.N. statistics that have been available. Here we go. Can you see there? It's China there, moving against better health there, improving there. All the green Latin American countries are moving towards smaller families. Your yellow ones here are the Arabic countries, and they get larger families, but they -- no, longer life, but not larger families. The Africans are the green down here. They still remain here. This is India. Indonesia's moving on pretty fast. (Laughter) And in the '80s here, you have Bangladesh still among the African countries there. But now, Bangladesh -- it's a miracle that happens in the '80s: the imams start to promote family planning. They move up into that corner. And in '90s, we have the terrible HIV epidemic that takes down the life expectancy of the African countries and all the rest of them move up into the corner, where we have long lives and small family, and we have a completely new world. (Applause)

　　這些數(shù)據(jù)都來自于聯(lián)合國 大家看到?jīng)]有? 這個是中國，他們在往上移動，健康狀況不斷改善 這些綠色的拉丁美洲國家 正朝向小家庭的方向移動 這些黃色的小球是阿拉伯國家 壽命在變長但家庭規(guī)模不變 非洲國家是下面的綠球，他們一直在下面 這個是印度 印度尼西亞的移動速度非?？?(笑聲) 80年代的時候 孟加拉國仍然和非洲國家在一起 但是80年代的奇跡發(fā)生在孟加拉國 媽媽們開始宣傳和普及計劃生育 他們向左上角移動 90年代恐怖的艾滋病流行 導致非洲國家的平均壽命縮短 而其他國家都向左上角移動 大家都有了長壽命和小家庭，而世界也煥然一新了 (掌聲)

　　Let me make a comparison directly between the United States of America and Vietnam. 1964: America had small families and long life; Vietnam had large families and short lives. And this is what happens: the data during the war indicate that even with all the death, there was an improvement of life expectancy. By the end of the year, the family planning started in Vietnam and they went for smaller families. And the United States up there is getting for longer life, keeping family size. And in the '80s now, they give up communist planning and they go for market economy, and it moves faster even than social life. And today, we have in Vietnam the same life expectancy and the same family size here in Vietnam, 2003, as in United States, 1974, by the end of the war. I think we all -- if we don't look in the data -- we underestimate the tremendous change in Asia, which was in social change before we saw the economical change.

　　現(xiàn)在我們對比一下美國和越南 1964年的美國家庭小壽命長 越南的家庭大而壽命短。這是后來的變化 越戰(zhàn)時期的數(shù)據(jù)顯示，盡管戰(zhàn)爭造成傷亡 越南人的平均壽命仍有提高 70年代末期 越南的計劃生育減小了家庭規(guī)模 美國人的平均壽命也在延長 而家庭規(guī)模不變 到了90年代 越南由計劃經(jīng)濟轉(zhuǎn)為市場經(jīng)濟 其經(jīng)濟發(fā)展的速度超過了社會的發(fā)展 今天(2003)越南人的平均壽命和家庭規(guī)模 已經(jīng)和越戰(zhàn)結束時(1974)的美國一樣 如果沒有看到這些數(shù)據(jù)的話 我們會低估了亞洲的巨大變化 這些超前于經(jīng)濟發(fā)展的社會變革

　　Let's move over to another way here in which we could display the distribution in the world of the income. This is the world distribution of income of people. One dollar, 10 dollars or 100 dollars per day. There's no gap between rich and poor any longer. This is a myth. There's a little hump here. But there are people all the way. And if we look where the income ends up -- the income -- this is 100 percent the world's annual income. And the richest 20 percent, they take out of that about 74 percent. And the poorest 20 percent, they take about two percent. And this shows that the concept of developing countries is extremely doubtful. We think about aid, like these people here giving aid to these people here. But in the middle, we have most the world population, and they have now 24 percent of the income.

　　下面我們換個視角 X軸顯示了全世界的收入分布 每天收入1美元，10美元和100美元 富與窮之間的鴻溝幾乎消失了，簡直是個奇跡 這里還有一個很小的峰，但總體上是均數(shù)分布的 我們看看收入的分配情況 這代表全世界人民每年的全部收入 最富有的20%那部分人 得到了全部收入的74% 最貧窮的20%那部分人 只得到2% 可見發(fā)展中國家的理念 極其的不確切 我們總以為最富的人應該給最窮的人提供援助 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%

　　We heard it in other forms. And who are these? Where are the different countries? I can show you Africa. This is Africa. 10 percent the world population, most in poverty. This is OECD. The rich country. The country club of the U.N. And they are over here on this side. Quite an overlap between Africa and OECD. And this is Latin America. It has everything on this Earth, from the poorest to the richest, in Latin America. And on top of that, we can put East Europe, we can put East Asia, and we put South Asia. And how did it look like if we go back in time, to about 1970? Then there was more of a hump. And we have most who lived in absolute poverty were Asians. The problem in the world was the poverty in Asia. And if I now let the world move forward, you will see that while population increase, there are hundreds of millions in Asia getting out of poverty and some others getting into poverty, and this is the pattern we have today. And the best projection from the World Bank is that this will happen, and we will not have a divided world. We'll have most people in the middle.

　　這是個老問題了，中間這些人是誰? 他們在哪些國家?先看非洲 非洲占世界人口的十分之一，多數(shù)是窮人 這個代表富裕的經(jīng)合組織成員國，聯(lián)合國俱樂部的會員 他們在這邊，很小一部分與非洲重疊 這是拉丁美洲，他們可以代表全世界 從最貧窮到最富有的人都在那里 再往上是東歐，東亞還有南亞 過去是什么樣子的呢? 如果我們回到1970年，這里有一個明顯的峰 這些絕對貧困的人群中 大多數(shù)是亞洲人 那時世界的問題就在于亞洲的貧窮 后來隨著人口的增長 數(shù)以億計的亞洲人擺脫了貧困 另外一些人卻陷入貧窮，這就是今天的世界 而這是世界銀行對未來最樂觀的預測 世界再也不是貧富懸殊的，大多數(shù)人擁有中等的收入

　　Of course it's a logarithmic scale here, but our concept of economy is growth with percent. We look upon it as a possibility of percentile increase. If I change this, and I take GDP per capita instead of family income, and I turn these individual data into regional data of gross domestic product, and I take the regions down here, the size of the bubble is still the population. And you have the OECD there, and you have sub-Saharan Africa there, and we take off the Arab states there, coming both from Africa and from Asia, and we put them separately, and we can expand this axis, and I can give it a new dimension here, by adding the social values there, child survival. Now I have money on that axis, and I have the possibility of children to survive there. In some countries, 99.7 percent of children survive to five years of age; others, only 70. And here it seems there is a gap between OECD, Latin America, East Europe, East Asia, Arab states, South Asia and sub-Saharan Africa. The linearity is very strong between child survival and money.

　　當然這是指數(shù)冪分布的圖 因為經(jīng)濟的增長是用百分比來衡量的 我們用百分比的變化來評估經(jīng)濟增長 下面把X軸改為人均國內(nèi)生產(chǎn)總值 個人的數(shù)據(jù)轉(zhuǎn)為各大洲的數(shù)據(jù) 球的大小代表人口的多少 這個是經(jīng)合組織國家，這是撒哈拉以南非洲 我們把阿拉伯國家 從非洲和亞洲單獨分出來 然后把X軸延伸一下 再加上一個新的維度 一個有社會價值的參數(shù) 兒童生存率 X軸代表經(jīng)濟 Y軸顯示兒童存活的比率 一些國家的99.7%的小孩 可以活到5歲以上 另一些國家只有70% 很明顯可以看到 經(jīng)合組織成員國 和拉丁美洲，東歐，東亞 阿拉伯國家，南亞 以及撒哈拉以南非洲地區(qū)的差距 兒童生存率和經(jīng)濟之間 聯(lián)系非常緊密

　　But let me split sub-Saharan Africa. Health is there and better health is up there. I can go here and I can split sub-Saharan Africa into its countries. And when it burst, the size of its country bubble is the size of the population. Sierra Leone down there. Mauritius is up there. Mauritius was the first country to get away with trade barriers, and they could sell their sugar -- they could sell their textiles -- on equal terms as the people in Europe and North America.

　　下面把撒哈拉以南非洲地區(qū) 分解成各個國家 分布靠上邊的國家 擁有更高的健康水平 撒哈拉以南的非洲各國是如此分布的 小球的尺寸代表該國人口 塞拉里昂在下邊 毛里求斯在上邊 毛里求斯是第一個消除了貿(mào)易壁壘的國家 他們的蔗糖和紡織品的貿(mào)易協(xié)定 與歐洲和北美一樣

　　There's a huge difference between Africa. And Ghana is here in the middle. In Sierra Leone, humanitarian aid. Here in Uganda, development aid. Here, time to invest; there, you can go for a holiday. It's a tremendous variation within Africa which we rarely often make -- that it's equal everything. I can split South Asia here. India's the big bubble in the middle. But a huge difference between Afghanistan and Sri Lanka. I can split Arab states. How are they? Same climate, same culture, same religion -- huge difference. Even between neighbors. Yemen, civil war. United Arab Emirate, money which was quite equally and well used. Not as the myth is. And that includes all the children of the foreign workers who are in the country. Data is often better than you think. Many people say data is bad. There is an uncertainty margin, but we can see the difference here: Cambodia, Singapore. The differences are much bigger than the weakness of the data. East Europe: Soviet economy for a long time, but they come out after 10 years very, very differently. And there is Latin America. Today, we don't have to go to Cuba to find a healthy country in Latin America. Chile will have a lower child mortality than Cuba within some few years from now. And here we have high-income countries in the OECD.

　　但是非洲內(nèi)部的差異非常巨大 加納在中部 塞拉里昂需要人道主義援助 烏干達則需要發(fā)展援助 在加納可以進行投資了 毛里求斯則可以去度假 非洲內(nèi)部的差異之大確實很驚人 而我們卻總以為 非洲國家都差不多 下面分解南亞各國 印度是中間的藍色大球 而斯里蘭卡和阿富汗有著巨大差異 把阿拉伯世界分解來看 盡管是相同的氣候，相同的文化 相同的宗教 卻有巨大的差異 也門在打內(nèi)戰(zhàn) 鄰國阿聯(lián)酋卻躺在錢堆里 而且(阿聯(lián)酋的)兒童健康數(shù)據(jù) 包含了所有的外籍勞工 大家總說數(shù)據(jù)不準確 數(shù)據(jù)其實比我們想象的好很多 數(shù)據(jù)是有誤差 但柬埔寨和新加坡的差距肯定遠大于數(shù)據(jù)的誤差 再看東歐 在蘇聯(lián)經(jīng)濟模式下發(fā)展了多年 但在過去10年 卻經(jīng)歷了巨大的變化 當今的拉丁美洲 古巴再也不是唯一的健康國家了 幾年后智利的兒童死亡率將低于古巴 這些是經(jīng)合組織成員國

　　And we get the whole pattern here of the world, which is more or less like this. And if we look at it, how it looks -- the world, in 1960, it starts to move. 1960. This is Mao Tse-tung. He brought health to China. And then he died. And then Deng Xiaoping came and brought money to China, and brought them into the mainstream again. And we have seen how countries move in different directions like this, so it's sort of difficult to get an example country which shows the pattern of the world. But I would like to bring you back to about here at 1960. I would like to compare South Korea, which is this one, with Brazil, which is this one. The label went away for me here. And I would like to compare Uganda, which is there. And I can run it forward, like this. And you can see how South Korea is making a very, very fast advancement, whereas Brazil is much slower.

　　這里顯示的就是我們的世界 大概就是這樣的情形 如果我們回到過去 看看世界是怎樣的 從1960年開始 1960年(中國有)毛澤東 他給中國帶來了健康 他去世后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 其他國家的移動方向也不盡相同 很難找出哪個國家 能代表全世界的發(fā)展模式 我們回到1960年做個比較 先選中韓國(左邊的小黃球)巴西(右邊的黃綠色大球) 烏干達(Y軸上面的小紅球) 隨著時間的推移，我們看到 韓國的發(fā)展速度非常非常快 巴西就慢得多

　　And if we move back again, here, and we put on trails on them, like this, you can see again that the speed of development is very, very different, and the countries are moving more or less in the same rate as money and health, but it seems you can move much faster if you are healthy first than if you are wealthy first. And to show that, you can put on the way of United Arab Emirate. They came from here, a mineral country. They cached all the oil; they got all the money; but health cannot be bought at the supermarket. You have to invest in health. You have to get kids into schooling. You have to train health staff. You have to educate the population. And Sheikh Sayed did that in a fairly good way. In spite of falling oil prices, he brought this country up here. So we've got a much more mainstream appearance of the world, where all countries tend to use their money better than they used in the past. Now, this is, more or less, if you look at the average data of the countries -- they are like this.

　　我們再回到過去 給每個球畫出運動的軌跡 可以看到，發(fā)展速度的差距非常大 雖然各國的經(jīng)濟和健康 發(fā)展的軌跡大同小異 但是健康水平起點較高的國家 發(fā)展速度遠超過經(jīng)濟水平起點高的 為了說明這一點 我們看看阿聯(lián)酋 他們從這里出發(fā) 一個資源型國家 他們靠石油大把賺錢 但健康絕不是超市里的貨物 需要衛(wèi)生方面的投資 需要提高兒童的教育水平 需要培訓衛(wèi)生工作者 還要教育民眾 Sheikh Sayed 干的非常漂亮 盡管油價下跌了 他仍改善了阿聯(lián)酋的健康 這里我們可以看到 世界發(fā)展的主流 各國對資金的分配和使用 都比過去合理的多 這里大家看到各國的數(shù)據(jù) 基本上都是平均數(shù)

　　Now that's dangerous, to use average data, because there is such a lot of difference within countries. So if I go and look here, we can see that Uganda today is where South Korea was 1960. If I split Uganda, there's quite a difference within Uganda. These are the quintiles of Uganda. The richest 20 percent of Ugandans are there. The poorest are down there. If I split South Africa, it's like this. And if I go down and look at Niger, where there was such a terrible famine, lastly, it's like this. The 20 percent poorest of Niger is out here, and the 20 percent richest of South Africa is there, and yet we tend to discuss on what solutions there should be in Africa. Everything in this world exists in Africa. And you can't discuss universal access to HIV [medicine] for that quintile up here with the same strategy as down here. The improvement of the world must be highly contextualized, and it's not relevant to have it on regional level. We must be much more detailed. We find that students get very excited when they can use this.

　　但是用平均數(shù)可能會很危險 因為國家內(nèi)部也存在很大的差異 我們看這里 今天的烏干達和1960年的韓國差不多 如果把烏干達分解開 可以看到內(nèi)部的明顯差異 烏干達最富有的20%在右邊 最貧窮的在左下邊 如果把南非分解開 尼日在下邊 他們剛遭受一場恐怖的饑荒 最貧窮的20%的尼日人在最左邊 而最富有的20%的南非人在最右邊 今天我們?nèi)匀辉谟懻?什么方案能解決非洲的問題 世界上所有的問題非洲都有 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 同時也適用于這些地方 世界的發(fā)展一定要因地制宜來分析 僅從各大洲的水平上來分析是不夠的 當學生們接觸到這個軟件的時候 他們都非常興奮

　　And even more policy makers and the corporate sectors would like to see how the world is changing. Now, why doesn't this take place? Why are we not using the data we have? We have data in the United Nations, in the national statistical agencies and in universities and other non-governmental organizations. Because the data is hidden down in the databases. And the public is there, and the Internet is there, but we have still not used it effectively.

　　此外，政策制定者，各企業(yè)部門 都會想知道世界的變化 但為什么大家仍然不知道(世界的變化) 為什么我們無法使用已知的數(shù)據(jù)呢 我們的聯(lián)合國，國家統(tǒng)計部門 學院還有非政府組織都擁有數(shù)據(jù) 但數(shù)據(jù)被隱藏在底層的數(shù)據(jù)庫里 而公眾在上面(太陽)互聯(lián)網(wǎng)在這里(地平線)并未得到有效的使用

　　All that information we saw changing in the world does not include publicly-funded statistics. There are some web pages like this, you know, but they take some nourishment down from the databases, but people put prices on them, stupid passwords and boring statistics. (Laughter) (Applause)

　　之前我們看到的 關于世界變化的信息 并不包括公眾資助的統(tǒng)計數(shù)據(jù) 的確有一些網(wǎng)站依靠數(shù)據(jù)庫的營養(yǎng)而存在著 但這是要收費的 還有愚蠢的密碼和討厭的統(tǒng)計表格 (笑聲，掌聲)

　　And this won't work. So what is needed? We have the databases. It's not the new database you need. We have wonderful design tools, and more and more are added up here. So we started a nonprofit venture which we called -- linking data to design -- we call it Gapminder, from the London underground, where they warn you, "mind the gap." So we thought Gapminder was appropriate. And we started to write software which could link the data like this. And it wasn't that difficult. It took some person years, and we have produced animations. You can take a data set and put it there. We are liberating U.N. data, some few U.N. organization.

　　這個是行不通的 我們需要什么? 數(shù)據(jù)庫是現(xiàn)成的 不需要新的數(shù)據(jù)庫 我們有很好的視覺軟件 還將有更多的問世 于是我們成立了一個非營利機構 我們稱之為“數(shù)據(jù)與圖樣的聯(lián)結” - Gapminder 靈感來自倫敦地鐵(他們提醒乘客“小心列車與站臺間的縫隙”) 而且我們制作了一個軟件 把數(shù)據(jù)和圖樣聯(lián)結起來 這個并不難 需要幾個人花幾年時間 建立數(shù)據(jù)庫后大家就能看到動畫 我們正嘗試解放聯(lián)合國的數(shù)據(jù)庫

　　Some countries accept that their databases can go out on the world, but what we really need is, of course, a search function. A search function where we can copy the data up to a searchable format and get it out in the world. And what do we hear when we go around? I've done anthropology on the main statistical units. Everyone says, "It's impossible. This can't be done. Our information is so peculiar in detail, so that cannot be searched as others can be searched. We cannot give the data free to the students, free to the entrepreneurs of the world." But this is what we would like to see, isn't it? The publicly-funded data is down here. And we would like flowers to grow out on the Net. And one of the crucial points is to make them searchable, and then people can use the different design tool to animate it there. And I have a pretty good news for you. I have a good news that the present, new Head of U.N. Statistics, he doesn't say it's impossible. He only says, "We can't do it." (Laughter) And that's a quite clever guy, huh? (Laughter)

　　少數(shù)聯(lián)合國機構和幾個國家已經(jīng)開放了數(shù)據(jù)庫 但我們最需要的是數(shù)據(jù)搜索引擎 依靠搜索引擎 我們先把原始數(shù)據(jù)復制成可搜索的格式 再把數(shù)據(jù)發(fā)布到全世界 外界對這個設想的反應如何呢? 我嘗試跟幾個大型統(tǒng)計機構交涉 所有人都說這是不可能的 “這行不通，我們的信息很獨特， 不可能像其它數(shù)據(jù)那樣檢索的出來 我們也不能免費把數(shù)據(jù)開放 給全世界的學生們和企業(yè)部門使用。” 但這正是我們期望看到的，不是嗎? 下邊是公眾資助采集的數(shù)據(jù) 我們希望互聯(lián)網(wǎng)上長出美麗的花朵 關鍵的一步 是讓這些數(shù)據(jù)可被搜索到 并借助軟件實現(xiàn)動畫的演示 我有個很好的消息要告訴大家 新上任的聯(lián)合國統(tǒng)計部門的領導 并沒有說這是不可能的 他只說“我們不能這么做。” (笑聲) 他很聰明吧 (笑聲)

　　So we can see a lot happening in data in the coming years. We will be able to look at income distributions in completely new ways. This is the income distribution of China, 1970. the income distribution of the United States, 1970. Almost no overlap. Almost no overlap. And what has happened? What has happened is this: that China is growing, it's not so equal any longer, and it's appearing here, overlooking the United States. Almost like a ghost, isn't it, huh? (Laughter)

　　未來幾年中 我們將會看到數(shù)據(jù)庫的變化 我們會用全新的視角 來看收入的分配 這是1970年中國的收入分配 這是1970年美國的收入分配 幾乎沒有重疊 后來呢? 中國在增長，再也不像以前那樣平等了 它出現(xiàn)在右邊，俯視著美國 是不是像個鬼一樣 (笑聲)

　　It's pretty scary. But I think it's very important to have all this information. We need really to see it. And instead of looking at this, I would like to end up by showing the Internet users per 1,000. In this software, we access about 500 variables from all the countries quite easily. It takes some time to change for this, but on the axises, you can quite easily get any variable you would like to have. And the thing would be to get up the databases free, to get them searchable, and with a second click, to get them into the graphic formats, where you can instantly understand them. Now, statisticians doesn't like it, because they say that this will not show the reality; we have to have statistical, analytical methods. But this is hypothesis-generating.

　　很嚇人吧 我認為這些信息很重要 大家很有必要看到這些 另外我最后要給大家展示 每千人中的網(wǎng)民數(shù)量 這個軟件能讓我們很容易的看到 全球各國的近500個參數(shù) 通過點擊坐標軸 你能輕易改變參數(shù)的設定 我們的初衷是 數(shù)據(jù)免費下載且易于查找 然后再點一下鼠標 數(shù)據(jù)就成為圖表的形式 那樣大家就可以 立刻看明白這些數(shù)據(jù)了 統(tǒng)計學家們不喜歡這樣子 他們認為這不能準確地反映事實 傳統(tǒng)的統(tǒng)計和分析方法是不能取代的 但數(shù)據(jù)動畫可以幫助提出假說

　　I end now with the world. There, the Internet is coming. The number of Internet users are going up like this. This is the GDP per capita. And it's a new technology coming in, but then amazingly, how well it fits to the economy of the countries. That's why the 100 dollar computer will be so important. But it's a nice tendency. It's as if the world is flattening off, isn't it? These countries are lifting more than the economy and will be very interesting to follow this over the year, as I would like you to be able to do with all the publicly funded data. Thank you very much. (Applause)

　　最后我們看一下當今的互聯(lián)網(wǎng)世界 網(wǎng)民數(shù)量不斷向上攀升(X軸是)人均國民生產(chǎn)總值 互聯(lián)網(wǎng)是一項新技術 但令人驚訝的是 它的普及和國家的經(jīng)濟水平極其一致 這也解釋了100美元電腦的重要性 但這是很好的趨勢 世界各國的差距將會縮小，不是嗎 這些國家的互聯(lián)網(wǎng)普及速度 超過了經(jīng)濟的發(fā)展速度 我也希望大家都可以 自由使用公眾資助采集的數(shù)據(jù) 非常感謝! (掌聲)