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TED2006

Hans Rosling: The best stats you've ever seen

ハンス・ロスリング 最高の統計を披露

February 22, 2006

統計データをこんな風に見せられたことはないでしょう。スポーツ実況者張りのドラマ性と緊迫感を込めて、統計の達人ハンス・ロスリングが「発展途上国」の神話を打ち崩します。

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. Full bio

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Double-click the English subtitles below to play the video.
About 10 years ago, I took on the task to teach global development
10年ほど前 私はスウェーデンの学生に 世界の発展について
00:25
to Swedish undergraduate students. That was after having spent
教える仕事に就きました 私がアフリカの機関と一緒に
00:29
about 20 years together with African institutions studying hunger in Africa,
20年ほどアフリカの飢餓の研究をしていたので
00:33
so I was sort of expected to know a little about the world.
世界のことを少しは知っていると期待したのでしょう
00:37
And I started in our medical university, Karolinska Institute,
医科大であるカロリンスカ研究所で「世界保健」という
00:41
an undergraduate course called Global Health. But when you get
学部の授業を持つことになりました しかしやる段になって
00:46
that opportunity, you get a little nervous. I thought, these students
不安になりました スウェーデンでも最も成績優秀な
00:50
coming to us actually have the highest grade you can get
学生たちが相手です 私が教える事なんか
00:53
in Swedish college systems -- so, I thought, maybe they know everything
みんな知っているのではないかと思いました
00:56
I'm going to teach them about. So I did a pre-test when they came.
そこで最初に小テストをやることにしました
00:59
And one of the questions from which I learned a lot was this one:
その時の質問は 私に多くのことを教えてくれました
01:03
"Which country has the highest child mortality of these five pairs?"
“この5組のそれぞれについて 乳幼児死亡率が高い方を選べ”
01:06
And I put them together, so that in each pair of country,
各組は 一方が他方よりも2倍以上
01:10
one has twice the child mortality of the other. And this means that
乳幼児死亡率が高くなるように選んであります
01:14
it's much bigger a difference than the uncertainty of the data.
差異が データの誤差よりずっと大きくなるようにしたのです
01:19
I won't put you at a test here, but it's Turkey,
別に皆さんをテストはしません
01:24
which is highest there, Poland, Russia, Pakistan and South Africa.
答えは トルコ、ポーランド、ロシア、パキスタン、南アフリカです
01:26
And these were the results of the Swedish students. I did it so I got
これがスウェーデンの学生の成績です
01:31
the confidence interval, which is pretty narrow, and I got happy,
信頼区間はごく狭く 私にはありがたい結果でした
01:34
of course: a 1.8 right answer out of five possible. That means that
5点満点で平均1.8です これなら
01:37
there was a place for a professor of international health --
世界保健の教授の居場所があります
01:41
(Laughter) and for my course.
私の授業も安泰です (笑)
01:44
But one late night, when I was compiling the report
しかしその結果について 本当に理解したのは
01:46
I really realized my discovery. I have shown
夜遅く その答案をまとめている時でした
01:50
that Swedish top students know statistically significantly less
スウェーデンの学生の世界の知識は 統計的有意に
01:54
about the world than the chimpanzees.
チンパンジーより低い ということです
01:59
(Laughter)
(笑)
02:01
Because the chimpanzee would score half right if I gave them
チンパンジーはバナナを2本もやれば スリランカかトルコか
02:03
two bananas with Sri Lanka and Turkey. They would be right half of the cases.
半分の場合は正しい方を選ぶでしょう
02:07
But the students are not there. The problem for me was not ignorance;
スウェーデンの学生はもっと下です 問題は無知ではなく
02:10
it was preconceived ideas.
先入観です
02:14
I did also an unethical study of the professors of the Karolinska Institute
私はカロリンスカ研究所の教授にも 非倫理的な調査を行いました
02:17
(Laughter)
(笑)
02:21
-- that hands out the Nobel Prize in Medicine,
ノーベル医学賞を授与する人たちが
02:22
and they are on par with the chimpanzee there.
チンパンジー並みだったのです
02:24
(Laughter)
(笑)
02:26
This is where I realized that there was really a need to communicate,
コミュニケーションの必要性を実感しました
02:29
because the data of what's happening in the world
世界各国の子供の健康水準については
02:33
and the child health of every country is very well aware.
よく整ったデータがあるからです
02:36
We did this software which displays it like this: every bubble here is a country.
それで ご覧のようなソフトを作りました 丸はそれぞれ国を表しています
02:39
This country over here is China. This is India.
これは中国で これはインドです
02:44
The size of the bubble is the population, and on this axis here I put fertility rate.
円の大きさは人口を表し 横軸は出生率です
02:50
Because my students, what they said
学生たちが 世界をどう捉えているのか
02:56
when they looked upon the world, and I asked them,
彼らに聞いてみました
02:59
"What do you really think about the world?"
“世界を実際どう思っているの?”
03:01
Well, I first discovered that the textbook was Tintin, mainly.
彼らの知識は「タンタンの冒険旅行」から来ているのが分かりました
03:03
(Laughter)
(笑)
03:07
And they said, "The world is still 'we' and 'them.'
学生たちは いまだ世界を「我々」と「彼ら」に分け
03:08
And we is Western world and them is Third World."
我々「西欧世界」 彼ら「第三世界」と考えています
03:11
"And what do you mean with Western world?" I said.
私は聞きました “その「西欧世界」というのは何?”
03:14
"Well, that's long life and small family, and Third World is short life and large family."
“長生きで小家族なのがそうです 短命で大家族なのが第三世界です”
03:17
So this is what I could display here. I put fertility rate here: number of children per woman:
これをご覧ください 横軸は出生率 女性1人当たりの子どもの数です
03:22
one, two, three, four, up to about eight children per woman.
1人、2人、3人、4人から8人まで
03:28
We have very good data since 1962 -- 1960 about -- on the size of families in all countries.
1962年以降の 各国の家族の大きさについては とても良いデータがあります
03:32
The error margin is narrow. Here I put life expectancy at birth,
誤差はわずかです 縦軸は出生時平均余命です
03:38
from 30 years in some countries up to about 70 years.
30歳くらいから 上は70歳くらいまであります
03:41
And 1962, there was really a group of countries here
1962年には 実際こういう国のグループがありました
03:45
that was industrialized countries, and they had small families and long lives.
工業国は 小家族で長寿です
03:48
And these were the developing countries:
そしてこっちは発展途上国
03:53
they had large families and they had relatively short lives.
大家族で比較的短命でした
03:55
Now what has happened since 1962? We want to see the change.
そして1962年以降何が起きたのか? 変化を見てみましょう
03:58
Are the students right? Is it still two types of countries?
学生たちは正しく 今も2種類の国があるのでしょうか?
04:02
Or have these developing countries got smaller families and they live here?
それとも発展途上国が小家族になって この辺にいるのか?
04:06
Or have they got longer lives and live up there?
あるいは長寿になって この上にいるのか?
04:09
Let's see. We stopped the world then. This is all U.N. statistics
見てみましょう データには利用可能な 国連の
04:11
that have been available. Here we go. Can you see there?
統計を使っています では見てみましょう
04:14
It's China there, moving against better health there, improving there.
これは中国 より健康な社会へと改善していきます
04:17
All the green Latin American countries are moving towards smaller families.
緑のラテンアメリカ諸国が 小家族に向かっています
04:20
Your yellow ones here are the Arabic countries,
黄色いのはアラブ諸国です
04:23
and they get larger families, but they -- no, longer life, but not larger families.
寿命が延びています
04:26
The Africans are the green down here. They still remain here.
緑色のアフリカは この場に留まったままです
04:30
This is India. Indonesia's moving on pretty fast.
インドに インドネシア とても速く動いています
04:33
(Laughter)
(笑)
04:36
And in the '80s here, you have Bangladesh still among the African countries there.
80年代に入ります バングラデシュはずっと
04:37
But now, Bangladesh -- it's a miracle that happens in the '80s:
アフリカ諸国と一緒でしたが ここで奇跡が起きます
04:40
the imams start to promote family planning.
イマームが家族計画を推進し
04:43
They move up into that corner. And in '90s, we have the terrible HIV epidemic
左上に上がっていきます 90年代にひどいHIVの流行があり
04:46
that takes down the life expectancy of the African countries
アフリカ諸国の平均余命が下がります
04:51
and all the rest of them move up into the corner,
残りの国はみな 左上へと進んでいきます
04:54
where we have long lives and small family, and we have a completely new world.
長寿で小家族 私たちの世界は全く違ったものになったのです
04:58
(Applause)
(拍手)
05:02
Let me make a comparison directly between the United States of America and Vietnam.
米国とベトナムとを比較してみましょう
05:15
1964: America had small families and long life;
1964年 米国は小家族で長寿
05:20
Vietnam had large families and short lives. And this is what happens:
一方ベトナムは大家族で短命です その後こうなります
05:25
the data during the war indicate that even with all the death,
戦争中のデータを見ると 戦争による多くの死者にも関わらず
05:29
there was an improvement of life expectancy. By the end of the year,
平均余命が伸びています 戦争が終わる頃に
05:35
the family planning started in Vietnam and they went for smaller families.
ベトナムで家族計画が始まり 小家族に向かいます
05:38
And the United States up there is getting for longer life,
米国は長寿で小さな家族を保っています
05:41
keeping family size. And in the '80s now,
ベトナムは80年代に
05:44
they give up communist planning and they go for market economy,
計画経済を捨てて市場経済になり
05:47
and it moves faster even than social life. And today, we have
社会水準の向上が加速します そして今日
05:50
in Vietnam the same life expectancy and the same family size
2003年のベトナムの平均余命と 家族の大きさは
05:54
here in Vietnam, 2003, as in United States, 1974, by the end of the war.
ベトナム戦争末 1974年の米国と同じ水準になりました
05:59
I think we all -- if we don't look in the data --
データを見なければ 我々は
06:06
we underestimate the tremendous change in Asia, which was
アジアの著しい変化を 過小評価することになります
06:10
in social change before we saw the economical change.
アジアでは 経済の変化の前に 社会の変化が現れています
06:14
Let's move over to another way here in which we could display
別な見方をしてみましょう 世界の所得の分布です
06:18
the distribution in the world of the income. This is the world distribution of income of people.
これは世界の人々の所得の分配を示しています
06:23
One dollar, 10 dollars or 100 dollars per day.
世帯1日当たり 1ドル、10ドル、100ドルです
06:30
There's no gap between rich and poor any longer. This is a myth.
もはや豊かな国と貧しい国の間にギャップはありません 神話です
06:35
There's a little hump here. But there are people all the way.
小さな谷がありますが ずっと途切れなく分布しています
06:39
And if we look where the income ends up -- the income --
所得がどういう配分になっているか見てみましょう
06:44
this is 100 percent the world's annual income. And the richest 20 percent,
これが世界の年間所得の100%です 最も豊かな20%が
06:48
they take out of that about 74 percent. And the poorest 20 percent,
74%を手にしています そして最も貧しい20%が
06:54
they take about two percent. And this shows that the concept
2%を手にしています これを見ると 発展途上国という概念は
07:01
of developing countries is extremely doubtful. We think about aid, like
非常に疑わしいことが分かります 援助について考えるとき
07:06
these people here giving aid to these people here. But in the middle,
私たちは ここの人たちが ここの人たちを助けていると思っています しかし真ん中の
07:10
we have most the world population, and they have now 24 percent of the income.
最も人口の多い部分が 今や24%の所得を得ているのです
07:15
We heard it in other forms. And who are these?
この人たちは誰なのでしょう?
07:19
Where are the different countries? I can show you Africa.
それぞれの国はどこにあたるのでしょう? まずアフリカです
07:23
This is Africa. 10 percent the world population, most in poverty.
これがアフリカ 世界の人口の10%で 大部分が貧困です
07:27
This is OECD. The rich country. The country club of the U.N.
これはOECD諸国 豊かな国々 国連のカントリークラブです
07:32
And they are over here on this side. Quite an overlap between Africa and OECD.
この部分で アフリカとOECDの間に 結構重なりがあります
07:37
And this is Latin America. It has everything on this Earth,
これは南アメリカ
07:42
from the poorest to the richest, in Latin America.
最貧から最富裕まで 全部そろっています
07:45
And on top of that, we can put East Europe, we can put East Asia,
さらに重ねて 東欧、東アジア、
07:48
and we put South Asia. And how did it look like if we go back in time,
南アジア 時間を1970年までを戻します
07:53
to about 1970? Then there was more of a hump.
谷が深くなっています
07:58
And we have most who lived in absolute poverty were Asians.
極貧生活をしている人はアジアに多くいました
08:03
The problem in the world was the poverty in Asia. And if I now let the world move forward,
世界の問題はアジアの貧困だったのです 時間を進めていくと
08:07
you will see that while population increase, there are
人口が増加していき アジアでは
08:14
hundreds of millions in Asia getting out of poverty and some others
何億という人々が貧困から抜け出し 別なところで
08:17
getting into poverty, and this is the pattern we have today.
貧困が進みます これが現在のパターンです
08:20
And the best projection from the World Bank is that this will happen,
世界銀行による最良の予測では この後こうなります
08:23
and we will not have a divided world. We'll have most people in the middle.
世界は分断されておらず ほとんどの人が真ん中にいます
08:27
Of course it's a logarithmic scale here,
これはもちろん対数目盛です
08:31
but our concept of economy is growth with percent. We look upon it
私たちの経済の概念では 成長をパーセントで計ります
08:33
as a possibility of percentile increase. If I change this, and I take
発展の割合として見るのです
08:38
GDP per capita instead of family income, and I turn these
横軸を世帯収入から 1人当たりのGDPに変えましょう
08:44
individual data into regional data of gross domestic product,
それぞれのデータを 地域のGDPに変えます
08:48
and I take the regions down here, the size of the bubble is still the population.
円の大きさは人口です
08:54
And you have the OECD there, and you have sub-Saharan Africa there,
OECDがここで サハラ以南のアフリカがここです
08:58
and we take off the Arab states there,
アラブ諸国を
09:01
coming both from Africa and from Asia, and we put them separately,
アフリカやアジアと分けて別にしましょう
09:04
and we can expand this axis, and I can give it a new dimension here,
横軸を引き伸ばし 次元をもう1つ追加します
09:08
by adding the social values there, child survival.
子供の生存率です
09:13
Now I have money on that axis, and I have the possibility of children to survive there.
横軸がお金で 縦軸が子どもの生き残る可能性です
09:16
In some countries, 99.7 percent of children survive to five years of age;
ある国々では99.7%の子どもが5歳以上まで生きられます
09:21
others, only 70. And here it seems there is a gap
一方70%の国々もあります ここにギャップがあるように見えます
09:25
between OECD, Latin America, East Europe, East Asia,
OECD、南アメリカ、東欧、東アジア
09:29
Arab states, South Asia and sub-Saharan Africa.
アラブ諸国、南アジア、サハラ以南のアフリカ
09:33
The linearity is very strong between child survival and money.
子どもの生存率とお金の間には強い相関があります
09:37
But let me split sub-Saharan Africa. Health is there and better health is up there.
サハラ以南のアフリカをバラしてみましょう 縦軸が保健の水準で 上に行くほど良いということです
09:42
I can go here and I can split sub-Saharan Africa into its countries.
サハラ以南アフリカを国に分けました
09:50
And when it burst, the size of its country bubble is the size of the population.
それぞれの円の大きさは国の人口を表しています
09:55
Sierra Leone down there. Mauritius is up there. Mauritius was the first country
シエラレオネがここ モーリシャスがあそこにあります
10:00
to get away with trade barriers, and they could sell their sugar --
モーリシャスは貿易障壁を最初に解除した国で
10:04
they could sell their textiles -- on equal terms as the people in Europe and North America.
砂糖や繊維製品を 欧米と対等な条件で売ることができます
10:08
There's a huge difference between Africa. And Ghana is here in the middle.
アフリカの国の間にも大きな差があるのです ガーナは真ん中あたり
10:13
In Sierra Leone, humanitarian aid.
シエラネオネは人道的支援を受けています
10:17
Here in Uganda, development aid. Here, time to invest; there,
ウガンダは開発支援を受けています この辺は投資できます
10:20
you can go for a holiday. It's a tremendous variation
ここでは休暇を過ごせます
10:25
within Africa which we rarely often make -- that it's equal everything.
アフリカには大きな幅があるのに 私たちは一緒くたにしています
10:28
I can split South Asia here. India's the big bubble in the middle.
南アジアを分割してみましょう 真ん中の大きな円がインドです
10:33
But a huge difference between Afghanistan and Sri Lanka.
アフガニスタンとスリランカでは 大変大きな違いがあります
10:37
I can split Arab states. How are they? Same climate, same culture,
アラブ諸国を分割してみましょう どうなるでしょう?
10:41
same religion -- huge difference. Even between neighbors.
気候、文化、宗教が同じでも 大きな違いがあります 隣国同士でも
10:45
Yemen, civil war. United Arab Emirate, money which was quite equally and well used.
イエメンは内戦 アラブ首長国連邦では 外国人労働者の子どもも含め
10:49
Not as the myth is. And that includes all the children of the foreign workers who are in the country.
お金が平等にうまく使われています 私たちが信じているのとは異なっています
10:54
Data is often better than you think. Many people say data is bad.
データはみんなが思うより有効なのです 不確実な部分があるにしても
11:01
There is an uncertainty margin, but we can see the difference here:
はっきりした差が見られます
11:06
Cambodia, Singapore. The differences are much bigger
このカンボジアとシンガポールの差は
11:08
than the weakness of the data. East Europe:
データの問題を はるかに超えています
11:11
Soviet economy for a long time, but they come out after 10 years
東欧は長い間ソビエト経済下にありましたが 離脱して10年
11:14
very, very differently. And there is Latin America.
大きく変わっています 南米も
11:20
Today, we don't have to go to Cuba to find a healthy country in Latin America.
今や健康な国はキューバだけではありません
11:23
Chile will have a lower child mortality than Cuba within some few years from now.
チリは数年のうちに 子供の死亡率の低さでキューバを抜きそうです
11:27
And here we have high-income countries in the OECD.
こちらは高所得なOECD諸国です
11:32
And we get the whole pattern here of the world,
これが世界全体のパターンです
11:35
which is more or less like this. And if we look at it,
だいたいこんな感じになっています
11:39
how it looks -- the world, in 1960, it starts to move. 1960.
1960年の世界を見てみましょう 動き始めます
11:44
This is Mao Tse-tung. He brought health to China. And then he died.
これは毛沢東です 中国に健康をもたらしました
11:50
And then Deng Xiaoping came and brought money to China, and brought them into the mainstream again.
彼の死後 鄧小平が出てきて 中国にお金をもたらし 中国を本流に引き戻しました
11:53
And we have seen how countries move in different directions like this,
このようにそれぞれの国が違った方向に動いています
11:58
so it's sort of difficult to get
ですから 世界の典型的なパターンを示す
12:02
an example country which shows the pattern of the world.
国の例を挙げるというのは難しいのです
12:06
But I would like to bring you back to about here at 1960.
また1960年に戻しましょう
12:11
I would like to compare South Korea, which is this one, with Brazil,
ここにある韓国と こちらにあるブラジルを比較してみましょう
12:17
which is this one. The label went away for me here. And I would like to compare Uganda,
比較のためウガンダも入れましょう
12:27
which is there. And I can run it forward, like this.
ここにあります 時間を進めます
12:32
And you can see how South Korea is making a very, very fast advancement,
韓国がいかに速く進歩しているか 分かるでしょう
12:37
whereas Brazil is much slower.
それに比べるとブラジルはずっとゆっくりです
12:46
And if we move back again, here, and we put on trails on them, like this,
また最初に戻って 航跡表示をオンにして
12:49
you can see again that the speed of development
もう一度実行すると 発展の速度が
12:55
is very, very different, and the countries are moving more or less
大きく異なるのが分かります そして経済と保健は
12:59
in the same rate as money and health, but it seems you can move
だいたいのところ同じ割合で変化しています
13:05
much faster if you are healthy first than if you are wealthy first.
しかし経済より保健が先に来る場合に 動きがずっと速いのが分かります
13:09
And to show that, you can put on the way of United Arab Emirate.
それが良くわかるように アラブ首長国連邦を加えてみましょう
13:14
They came from here, a mineral country. They cached all the oil;
資源の豊かな国です 石油でお金はできましたが
13:18
they got all the money; but health cannot be bought at the supermarket.
健康をスーパーマーケットで買うことはできません
13:21
You have to invest in health. You have to get kids into schooling.
健康に投資し 子どもたちを学校で教えなければなりません
13:25
You have to train health staff. You have to educate the population.
医療スタッフを育て 国民を教育しなければなりません
13:29
And Sheikh Sayed did that in a fairly good way.
首長ザーイドはこれをかなりうまくやりました
13:32
In spite of falling oil prices, he brought this country up here.
石油価格の下落にも関わらず この国をここまで引き上げたのです
13:35
So we've got a much more mainstream appearance of the world,
だから世界の主流の状況としては
13:39
where all countries tend to use their money
各国は昔に比べて
13:43
better than they used in the past. Now, this is, more or less,
お金をうまく使うようになっています
13:45
if you look at the average data of the countries -- they are like this.
これは各国をその平均で見た場合です
13:50
Now that's dangerous, to use average data, because there is such a lot
でも平均データを使うのは危険があります
13:57
of difference within countries. So if I go and look here, we can see
国の中にも大きな差があるからです これを見ると
14:02
that Uganda today is where South Korea was 1960. If I split Uganda,
現在のウガンダは 1960年に韓国がいた場所にいます
14:08
there's quite a difference within Uganda. These are the quintiles of Uganda.
ウガンダを分けると 国内に大きな差があります
14:14
The richest 20 percent of Ugandans are there.
ウガンダで最も富裕な20%がここ
14:19
The poorest are down there. If I split South Africa, it's like this.
最も貧しい層はここです 南アフリカを分けるとこんな感じです
14:22
And if I go down and look at Niger, where there was such a terrible famine,
最近ひどい飢饉のあったニジェールを見てみましょう
14:26
lastly, it's like this. The 20 percent poorest of Niger is out here,
ニジェールの最貧の20%はここで
14:31
and the 20 percent richest of South Africa is there,
南アフリカの最も豊かな20%はここです
14:36
and yet we tend to discuss on what solutions there should be in Africa.
それなのに私たちは アフリカに対する解決策は どうあるべきかと議論しています
14:39
Everything in this world exists in Africa. And you can't
アフリカには世界の全てがあります
14:44
discuss universal access to HIV [medicine] for that quintile up here
HIV対策について こっちの20%と一緒の議論を
14:47
with the same strategy as down here. The improvement of the world
こっちの20%にはできないのです
14:51
must be highly contextualized, and it's not relevant to have it
世界の改善は それぞれのコンテキストに合わせる必要があり
14:55
on regional level. We must be much more detailed.
大きな地域でくくるのは不適切です 細かくやらなきゃいけません
15:00
We find that students get very excited when they can use this.
このツールを使わせると 学生がとてもワクワクするのに気づきました
15:03
And even more policy makers and the corporate sectors would like to see
政策立案者や企業もまた 世界の変化を知りたがっています
15:07
how the world is changing. Now, why doesn't this take place?
ではなぜ それが実現しないのでしょう?
15:12
Why are we not using the data we have? We have data in the United Nations,
なぜ 既に持っているデータを使おうとしないのか?
15:16
in the national statistical agencies
国連も 国の統計機関も
15:20
and in universities and other non-governmental organizations.
大学も その他の非政府組織も データを持っているというのに
15:22
Because the data is hidden down in the databases.
それはデータが隠されているからです
15:26
And the public is there, and the Internet is there, but we have still not used it effectively.
一般の人々が使えるインターネットがあるというのに データは有効に使われていません
15:28
All that information we saw changing in the world
私たちが見てきた 世界の変化を示す情報に
15:33
does not include publicly-funded statistics. There are some web pages
公的にアクセスできるものはありません ある種のウェブページはあります
15:36
like this, you know, but they take some nourishment down from the databases,
データベースから養分を取っているわけですが
15:40
but people put prices on them, stupid passwords and boring statistics.
高い値段を付け 変なパスワードをかけ 退屈な統計データを表示するだけです
15:46
(Laughter) (Applause)
(笑と拍手)これではうまくいきません
15:51
And this won't work. So what is needed? We have the databases.
何が必要なのか? データベースはあります 新しいデータベースが
15:54
It's not the new database you need. We have wonderful design tools,
必要なわけではありません 素晴らしいデザインツールもあり
15:58
and more and more are added up here. So we started
どんどん増えています ですから私たちは
16:02
a nonprofit venture which we called -- linking data to design --
データをデザインに結び付ける 非営利のベンチャーを始めました
16:05
we call it Gapminder, from the London underground, where they warn you,
Gapminderです ロンドン地下鉄の“MIND THE GAP”
16:10
"mind the gap." So we thought Gapminder was appropriate.
(隙間にご注意ください)から名前を取りました
16:13
And we started to write software which could link the data like this.
私たちはデータをつなげられる ソフトを作り始めました
16:16
And it wasn't that difficult. It took some person years, and we have produced animations.
そんなに難しくはありません 数人年です それでデータを引き出し
16:20
You can take a data set and put it there.
アニメーションできるようになりました
16:26
We are liberating U.N. data, some few U.N. organization.
いくつか国連機関のデータも解放しました
16:28
Some countries accept that their databases can go out on the world,
いくつかの国は データを世界に公開することに同意しています
16:33
but what we really need is, of course, a search function.
しかし本当に必要なのは検索機能です
16:37
A search function where we can copy the data up to a searchable format
データを検索可能な形にして公開し 自由に検索できるようにしなければなりません
16:40
and get it out in the world. And what do we hear when we go around?
そのために世界を回って どんな言葉を耳にするでしょう?
16:45
I've done anthropology on the main statistical units. Everyone says,
私は統計機関の人類学に詳しくなりました みんな同じことを言います
16:48
"It's impossible. This can't be done. Our information is so peculiar
“不可能です うちの情報は特殊ですから”
16:53
in detail, so that cannot be searched as others can be searched.
“よそのデータのように検索可能にするのは無理です”
16:57
We cannot give the data free to the students, free to the entrepreneurs of the world."
“学生や世界の起業家に データを無料で提供はできません”
17:00
But this is what we would like to see, isn't it?
しかし私はそうしたいのです
17:05
The publicly-funded data is down here.
公的資金によるデータがここにあり
17:08
And we would like flowers to grow out on the Net.
それがネット上で花開くのを見たいのです
17:11
And one of the crucial points is to make them searchable, and then people can use
肝心なのは データを検索可能にし 様々なデザインツールを使い
17:14
the different design tool to animate it there.
絵として見られるようにすることです
17:19
And I have a pretty good news for you. I have a good news that the present,
良い報せがあります 国連統計局の新局長は
17:21
new Head of U.N. Statistics, he doesn't say it's impossible.
不可能だとは言いません 彼はただ
17:26
He only says, "We can't do it."
“我々には無理です”と言うだけです
17:30
(Laughter)
(笑)
17:32
And that's a quite clever guy, huh?
なかなか頭の良い人ですよね?
17:36
(Laughter)
(笑)
17:38
So we can see a lot happening in data in the coming years.
今後数年で データの方面で 多くのことが起こるでしょう
17:40
We will be able to look at income distributions in completely new ways.
所得分布を まったく違った方法で見られるようになるでしょう
17:44
This is the income distribution of China, 1970.
紫は1970年の中国の所得分布で
17:48
the income distribution of the United States, 1970.
水色は1970年の米国の所得分布です
17:54
Almost no overlap. Almost no overlap. And what has happened?
ほとんど重なりはありません その後どうなったでしょう?
17:59
What has happened is this: that China is growing, it's not so equal any longer,
こうなります 中国は成長し 平等ではなくなっていきます
18:03
and it's appearing here, overlooking the United States.
そしてこのような位置に 米国のすぐ背後に迫っています
18:08
Almost like a ghost, isn't it, huh?
なんだか お化けのようですね
18:12
(Laughter)
(笑)
18:14
It's pretty scary. But I think it's very important to have all this information.
結構怖い感じです このような情報を持つのは大変重要だと思います
18:16
We need really to see it. And instead of looking at this,
本当に見る必要があります 最後に
18:26
I would like to end up by showing the Internet users per 1,000.
1000人当たりの インターネットユーザ数を ご覧いただきましょう
18:32
In this software, we access about 500 variables from all the countries quite easily.
このソフトを使うと 世界の国々の500種のデータに 容易にアクセスできます
18:37
It takes some time to change for this,
画面の切り替えに若干時間がかかりますが
18:42
but on the axises, you can quite easily get any variable you would like to have.
縦軸と横軸に 好きなデータを選択できます
18:46
And the thing would be to get up the databases free,
必要なのはデータベースを無料化し 検索可能にすることで
18:51
to get them searchable, and with a second click, to get them
そうすれば クリックするだけで
18:56
into the graphic formats, where you can instantly understand them.
グラフに変えて 即座に理解できるようになります
18:59
Now, statisticians doesn't like it, because they say that this
統計学者はこういうのを気に入りません
19:04
will not show the reality; we have to have statistical, analytical methods.
現実を表していないと言います 統計的 分析的手法を使うべきだと言います
19:07
But this is hypothesis-generating.
しかし これで仮説生成ができるのです
19:16
I end now with the world. There, the Internet is coming.
インターネットが現れ インターネットにアクセスする
19:19
The number of Internet users are going up like this. This is the GDP per capita.
ユーザ数が増えていきます 横軸は1人当たりのGDPです
19:23
And it's a new technology coming in, but then amazingly, how well
新しく登場した技術ですが それが驚くほど
19:27
it fits to the economy of the countries. That's why the 100 dollar
国の経済力に対応しています だからこそ100ドルPCが
19:32
computer will be so important. But it's a nice tendency.
重要なのです ここには良い傾向が見えます
19:37
It's as if the world is flattening off, isn't it? These countries
世界がフラットになっているかのようです
19:40
are lifting more than the economy and will be very interesting
これらの国々は 経済以上に上昇しており
19:43
to follow this over the year, as I would like you to be able to do
今後どうなるか興味深いところです みんながすべての公的データを
19:46
with all the publicly funded data. Thank you very much.
使えるようになることを願っています
19:50
(Applause)
(拍手)
19:53
Reviewer:Yasushi Aoki

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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 will have their perspectives shifted by Hans Rosling. A professor of global health at Sweden's Karolinska Institute, his current work focuses on dispelling common myths about the so-called developing world, which (he points 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 sets Rosling apart isn't just his apt observations of broad social and economic trends, but the stunning way he presents them. Guaranteed: You've never seen data presented like this. By any logic, 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 are grounded in solid statistics (often drawn from United Nations 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 takes 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.

As if all this weren't enough, the irrepressible Rosling is also an accomplished sword-swallower — a skill he demonstrated at TED2007.


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