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  • Today, actually, is a very special day for me,

    譯者: Lilian Chiu 審譯者: Sharon Hsiao

  • because it is my birthday.

    今天對我來說是個很特別的一天,

  • (Applause)

    因為今天是我的生日。

  • And so, thanks to all of you for joining the party.

    (掌聲)

  • (Laughter)

    謝謝大家來參加這場派對。

  • But every time you throw a party, there's someone there to spoil it. Right?

    (笑聲)

  • (Laughter)

    但,每次你辦派對時, 總會掃興的人,對吧?

  • And I'm a physicist,

    (笑聲)

  • and this time I brought another physicist along to do so.

    我是物理學家,

  • His name is Albert Einstein -- also Albert -- and he's the one who said

    這次,我帶來了 另一位來掃興的物理學家。

  • that the person who has not made his great contributions to science

    他叫做阿爾伯特愛因斯坦—— 也叫阿爾伯特——他說過

  • by the age of 30

    如果一個人到了三十歲 都還沒有對科學

  • will never do so.

    做出偉大的貢獻, 就永遠不會有貢獻了。

  • (Laughter)

    (笑聲)

  • Now, you don't need to check Wikipedia

    各位不需要去維基百科查證,

  • that I'm beyond 30.

    我已經超過三十歲了。

  • (Laughter)

    (笑聲)

  • So, effectively, what he is telling me, and us,

    所以,實際上,他要 告訴我以及我們的是,

  • is that when it comes to my science,

    在我的科學領域中,

  • I'm deadwood.

    我已經是枯枝。

  • Well, luckily, I had my share of luck within my career.

    嗯,幸運的是,我在 我的職涯中有好運氣。

  • Around age 28, I became very interested in networks,

    大約二十八歲時, 我對於網路非常感興趣,

  • and a few years later, we managed to publish a few key papers

    幾年後,我們出版了 幾篇重要論文,

  • that reported the discovery of scale-free networks

    闡述我們發現了無尺度網路,

  • and really gave birth to a new discipline that we call network science today.

    創造出了一門新的學科, 就是現今所稱的網路科學。

  • And if you really care about it, you can get a PhD now in network science

    如果各位想知道,現在可以 取得網路科學博士學位的地方

  • in Budapest, in Boston,

    包括布達佩斯、波士頓,

  • and you can study it all over the world.

    且在全世界各地都可以研讀它。

  • A few years later,

    幾年後,

  • when I moved to Harvard first as a sabbatical,

    我搬到哈佛,一開始是學術休假,

  • I became interested in another type of network:

    我開始對另一種網路產生了興趣:

  • that time, the networks within ourselves,

    我們體內的網路,

  • how the genes and the proteins and the metabolites link to each other

    基因、蛋白質、代謝物 彼此之間如何連結,

  • and how they connect to disease.

    以及它們和疾病的關係。

  • And that interest led to a major explosion within medicine,

    那項興趣導致了醫學上的大爆炸,

  • including the Network Medicine Division at Harvard,

    包括哈佛的網路醫學部門,

  • that has more than 300 researchers who are using this perspective

    有超過三百名研究者使用這種觀點

  • to treat patients and develop new cures.

    來治療病人和開發新解藥。

  • And a few years ago,

    幾年前,

  • I thought that I would take this idea of networks

    我認為我可以把網路的這個點子

  • and the expertise we had in networks

    以及我們對網路的專長 帶到不同的領域去,

  • in a different area,

    也就是,用來了解成功。

  • that is, to understand success.

    為什麼要那樣做?

  • And why did we do that?

    嗯,我們認為,在某種程度上,

  • Well, we thought that, to some degree,

    我們的成功是由我們所屬的網路決定,

  • our success is determined by the networks we're part of --

    我們的網路將我們向前推進, 也可以讓我們遲滯不前。

  • that our networks can push us forward, they can pull us back.

    我很好奇,我們是否 能用這知識和大數據

  • And I was curious if we could use the knowledge and big data and expertise

    及我們開發網路的專門技術 來將成功的發生給量化。

  • where we develop the networks

    這就是研究的結果。

  • to really quantify how these things happen.

    各位現在看到的是 博物館的畫廊的網路,

  • This is a result from that.

    它們彼此連結。

  • What you see here is a network of galleries in museums

    透過我們去年畫的這張地圖,

  • that connect to each other.

    我們就可以很精確地預測 一位藝術家是否會成功,

  • And through this map that we mapped out last year,

    只要給我這位藝術家 在職涯中的最早五件展示品。

  • we are able to predict very accurately the success of an artist

    當我們在思考成功時,

  • if you give me the first five exhibits that he or she had in their career.

    我們發現,成功不只和網路有關;

  • Well, as we thought about success,

    還有好多其他的維度。

  • we realized that success is not only about networks;

    很顯然,我們想要成功 就一定需要的一樣東西

  • there are so many other dimensions to that.

    就是表現。

  • And one of the things we need for success, obviously,

    所以,咱們來定義一下 表現和成功之間的差別。

  • is performance.

    表現是你所做的事:

  • So let's define what's the difference between performance and success.

    你能跑多快、你畫出什麼樣的畫、

  • Well, performance is what you do:

    你出版什麼樣的論文。

  • how fast you run, what kind of paintings you paint,

    然而,根據我們的工作定義,

  • what kind of papers you publish.

    成功的重點在於大家 能注意到你做了什麼、

  • However, in our working definition,

    你的表現如何:

  • success is about what the community notices from what you did,

    怎麼認可你的表現, 你的表現帶給你什麼報償?

  • from your performance:

    換言之,

  • How does it acknowledge it, and how does it reward you for it?

    你的表現是你的事, 但你的成功是我們所有人的事。

  • In other terms,

    這對我們來說是很重要的轉變,

  • your performance is about you, but your success is about all of us.

    因為當我們把成功定義為

  • And this was a very important shift for us,

    團體提供我們的一個集體測量值, 它就變成可測量的,

  • because the moment we defined success as being a collective measure

    因為如果它是在團體中, 就有相關的許多資料點。

  • that the community provides to us,

    所以我們去學校, 我們做作業,我們練習,

  • it became measurable,

    因為我們相信表現會導致成功。

  • because if it's in the community, there are multiple data points about that.

    但我們這樣開始探究之後,

  • So we go to school, we exercise, we practice,

    便了解到在數學問題上,

  • because we believe that performance leads to success.

    表現和成功非常不同。

  • But the way we actually started to explore,

    讓我說明一下。

  • we realized that performance and success are very, very different animals

    各位在這裡看到的是世界上 最快的人,尤塞恩博爾特。

  • when it comes to the mathematics of the problem.

    當然,他參加的比賽, 他大部分都有贏。

  • And let me illustrate that.

    我們知道他跑得最快,因為我們 有精密計時器來測量速度。

  • So what you see here is the fastest man on earth, Usain Bolt.

    關於他,有一點很有趣, 那就是當他贏的時候,

  • And of course, he wins most of the competitions that he enters.

    他並不是明顯超越他的對手許多。

  • And we know he's the fastest on earth because we have a chronometer

    他最多是比輸家快 1% 而已。

  • to measure his speed.

    他不僅只比第二名快 1%,

  • Well, what is interesting about him is that when he wins,

    他也沒有跑得比我快十倍——

  • he doesn't do so by really significantly outrunning his competition.

    我不是個好跑者,相信我。

  • He's running at most a percent faster than the one who loses the race.

    (笑聲)

  • And not only does he run only one percent faster than the second one,

    每當我們能夠測量表現時,

  • but he doesn't run 10 times faster than I do --

    我們就會注意到一件很有趣的事;

  • and I'm not a good runner, trust me on that.

    那就是,表現是受限的。

  • (Laughter)

    意思就是說,人類的表現 並沒有太大的變動。

  • And every time we are able to measure performance,

    人類表現只在一個小範圍中變動,

  • we notice something very interesting;

    我們的確需要很精密的 計時器才能測出差別。

  • that is, performance is bounded.

    這並不是說我們分不出 好和最好的差別,

  • What it means is that there are no huge variations in human performance.

    而是很難分辨出最好的人。

  • It varies only in a narrow range,

    那所造成的問題就是, 我們大部分人工作的領域中

  • and we do need the chronometer to measure the differences.

    並沒有精密的計時器 來測量我們的表現。

  • This is not to say that we cannot see the good from the best ones,

    好,表現是受限的,

  • but the best ones are very hard to distinguish.

    我們之間在表現上 沒有很大的差異。

  • And the problem with that is that most of us work in areas

    那成功呢?

  • where we do not have a chronometer to gauge our performance.

    咱們切換到一個不同的 主題,以書籍為例。

  • Alright, performance is bounded,

    對作家來說,成功的測量值之一 就是有多少人讀你的作品。

  • there are no huge differences between us when it comes to our performance.

    我的上一本書在 2009 年推出時,

  • How about success?

    我在歐洲跟我的編輯談,

  • Well, let's switch to a different topic, like books.

    我很感興趣:競爭對手是誰?

  • One measure of success for writers is how many people read your work.

    我有一些很棒的對手。

  • And so when my previous book came out in 2009,

    那週——

  • I was in Europe talking with my editor,

    (笑聲)

  • and I was interested: Who is the competition?

    丹布朗推出《失落的符號》,

  • And I had some fabulous ones.

    《最後一首歌》也推出了,

  • That week --

    尼可拉斯史派克的作品。

  • (Laughter)

    當你只是看列表,

  • Dan Brown came out with "The Lost Symbol,"

    你會知道,就表現來說,

  • and "The Last Song" also came out,

    這些書和我的書之間 幾乎沒有什麼差別。

  • Nicholas Sparks.

    對吧?

  • And when you just look at the list,

    所以,也許尼可拉斯史派克的 團隊更努力一點,

  • you realize, you know, performance-wise, there's hardly any difference

    他很容易成為第一名,

  • between these books or mine.

    因為誰會在頂端幾乎都是意外。

  • Right?

    所以,我說,咱們來看看數字, 我是研究資料的人,對吧?

  • So maybe if Nicholas Sparks's team works a little harder,

    咱們來看看尼可拉斯 史派克的銷售額如何。

  • he could easily be number one,

    結果發現,在第一個週末,

  • because it's almost by accident who ended up at the top.

    尼可拉斯史派克 賣出了超過十萬本書,

  • So I said, let's look at the numbers -- I'm a data person, right?

    這個數字很驚人。

  • So let's see what were the sales for Nicholas Sparks.

    只要一週銷售一萬本,

  • And it turns out that that opening weekend,

    就可以登上《紐約時報》 暢銷書排行榜了,

  • Nicholas Sparks sold more than a hundred thousand copies,

    所以他超越了成為第一名 需要的數字足足十倍。

  • which is an amazing number.

    但,他並非第一名。為什麼?

  • You can actually get to the top of the "New York Times" best-seller list

    因為還有丹布朗,那個週末, 他的書賣了一百二十萬本。

  • by selling 10,000 copies a week,

    (笑聲)

  • so he tenfold overcame what he needed to be number one.

    我喜歡這些數字是因為,

  • Yet he wasn't number one.

    它呈現出成功是沒有限制的,

  • Why?

    第一名並不會只比第二名多一點,

  • Because there was Dan Brown, who sold 1.2 million copies that weekend.

    而是用指數倍數來算,

  • (Laughter)

    因為成功是集體的測量值。

  • And the reason I like this number is because it shows that, really,

    我們把成功給他們,而不是 透過自己的表現贏來成功的。

  • when it comes to success, it's unbounded,

    我們了解到,表現, 也就是我們所做的,會受限,

  • that the best doesn't only get slightly more than the second best

    但成功,是集體的,沒有限制,

  • but gets orders of magnitude more,

    這就會讓人納悶:

  • because success is a collective measure.

    如果在表現上只能有小小的差別,

  • We give it to them, rather than we earn it through our performance.

    在成功上如何造成 這麼巨大的差別?

  • So one of things we realized is that performance, what we do, is bounded,

    最近,我出版了一本書, 就是針對這個問題而寫的。

  • but success, which is collective, is unbounded,

    他們沒有給我足夠的時間 去談所有這些,

  • which makes you wonder:

    所以我要回到這個問題,

  • How do you get these huge differences in success

    好,你有成功;它會何時出現?

  • when you have such tiny differences in performance?

    咱們回到讓派對掃興的 那個人,問問我們自己:

  • And recently, I published a book that I devoted to that very question.

    為什麼愛因斯坦 會說出那句荒謬的話,

  • And they didn't give me enough time to go over all of that,

    說只有在三十歲之前 你才可能真的有創意?

  • so I'm going to go back to the question of,

    因為他看看自己身邊, 這些很出色的物理學家,

  • alright, you have success; when should that appear?

    發明了量子力學和近代物理的人,

  • So let's go back to the party spoiler and ask ourselves:

    他們提出發明時都是 二十多歲或三十初頭。

  • Why did Einstein make this ridiculous statement,

    不只是他而已。

  • that only before 30 you could actually be creative?

    這並不是觀察偏見,

  • Well, because he looked around himself and he saw all these fabulous physicists

    因為有一整個領域的天才研究

  • that created quantum mechanics and modern physics,

    記錄這個事實,

  • and they were all in their 20s and early 30s when they did so.

    如果我們去看我們 所欣賞的過去人物,

  • And it's not only him.

    看看他們做出最大貢獻的年齡,

  • It's not only observational bias,

    不論是音樂、不論是科學、

  • because there's actually a whole field of genius research

    不論是工程,

  • that has documented the fact that,

    大部分都是在二、三十歲時達成,

  • if we look at the people we admire from the past

    最多四十初頭。

  • and then look at what age they made their biggest contribution,

    但這種天才研究有一個問題。

  • whether that's music, whether that's science,

    首先,它讓我們有一種印象,

  • whether that's engineering,

    認為創意等同年輕,

  • most of them tend to do so in their 20s, 30s, early 40s at most.

    這很痛,對吧?

  • But there's a problem with this genius research.

    (笑聲)

  • Well, first of all, it created the impression to us

    它也有存在觀察偏見,

  • that creativity equals youth,

    因為它只研究天才, 沒有研究一般科學家,

  • which is painful, right?

    且沒有研究我們所有人並問:

  • (Laughter)

    真的在我們年長之後 創意就消失嗎?

  • And it also has an observational bias,

    那就是我們試圖要做的,

  • because it only looks at geniuses and doesn't look at ordinary scientists

    能真正有參考是很重要的。

  • and doesn't look at all of us and ask,

    咱們來看看一般的 科學家,像我自己,

  • is it really true that creativity vanishes as we age?

    來看看我的職涯。

  • So that's exactly what we tried to do,

    這裡是我出版過的所有論文,

  • and this is important for that to actually have references.

    我的第一篇論文在 1989 年出版,

  • So let's look at an ordinary scientist like myself,

    當時我還在羅馬尼亞,

  • and let's look at my career.

    直到今年。

  • So what you see here is all the papers that I've published

    垂直來看,可以看到論文的影響,

  • from my very first paper, in 1989; I was still in Romania when I did so,

    也就是引用數,

  • till kind of this year.

    有多少篇其他論文 曾經引用過那篇文章。

  • And vertically, you see the impact of the paper,

    如果去看那些,就會發現 我的職涯大致可以分為三個階段。

  • that is, how many citations,

    前十年,我很努力工作, 沒有很高的成就。

  • how many other papers have been written that cited that work.

    似乎沒有人在乎我做什麼,對吧?

  • And when you look at that,

    幾乎沒有任何影響力。

  • you see that my career has roughly three different stages.

    (笑聲)

  • I had the first 10 years where I had to work a lot

    那段時間,我在做材料科學,

  • and I don't achieve much.

    接著,我發現了網路,

  • No one seems to care about what I do, right?

    接著開始出版網路的文章。

  • There's hardly any impact.

    導致了一篇又一篇的 高影響力論文出現。

  • (Laughter)

    感覺真的很好,我職涯的那個階段。

  • That time, I was doing material science,

    (笑聲)

  • and then I kind of discovered for myself networks

    問題是,現在會發生什麼事?

  • and then started publishing in networks.

    我們不知道,因為 還沒有經過那麼多時間,

  • And that led from one high-impact paper to the other one.

    無法得知那些論文的影響會有 多大;那需要時間才能知道。

  • And it really felt good. That was that stage of my career.

    如果去看資料,似乎,愛因斯坦, 那些天才研究,是對的,

  • (Laughter)

    我正在職涯的那個階段。

  • So the question is, what happens right now?

    (笑聲)

  • And we don't know, because there hasn't been enough time passed yet

    所以,我們說,好,

  • to actually figure out how much impact those papers will get;

    咱們來研究看看這是如何發生的,

  • it takes time to acquire.

    先看科學。

  • Well, when you look at the data,

    為了避免選樣偏誤,

  • it seems to be that Einstein, the genius research, is right,

    只去研究天才,

  • and I'm at that stage of my career.

    我們最後為每一位 科學家都重建了職涯,

  • (Laughter)

    從 1900 年至今的所有科學家,

  • So we said, OK, let's figure out how does this really happen,

    並針對所有科學家, 找出他們個人的顛峰時期,

  • first in science.

    不論他們是否有得到諾貝爾獎,

  • And in order not to have the selection bias,

    或者即使他們在顛峰時 也沒有人知道他們做了什麼。

  • to look only at geniuses,

    那就是這張投影片呈現的。

  • we ended up reconstructing the career of every single scientist

    每一條線就是一段職涯,

  • from 1900 till today

    淡藍色的點就是那職涯的顛峰,

  • and finding for all scientists what was their personal best,

    那是他們個人的最佳狀態。

  • whether they got the Nobel Prize or they never did,

    問題是,他們何時 有最重大的發現?

  • or no one knows what they did, even their personal best.

    為了量化它,我們去研究 做出最重大發現的機率,

  • And that's what you see in this slide.

    比如,你的職涯開始之後的 一、二、三,或十年?

  • Each line is a career,

    我們研究的不是真實年齡, 而是所謂的「學術年齡」。

  • and when you have a light blue dot on the top of that career,

    你的學術年齡開始於 你的第一篇論文被刊出時。

  • it says that was their personal best.

    我知道在座還有一些嬰兒。

  • And the question is,

    (笑聲)

  • when did they actually make their biggest discovery?

    咱們來看看你出版

  • To quantify that,

    最有影響力的論文的機率。

  • we look at what's the probability that you make your biggest discovery,

    各位可以看見,的確, 天才研究是對的。

  • let's say, one, two, three or 10 years into your career?

    大部分的科學家傾向會在 職涯的前十、十五年

  • We're not looking at real age.

    出版他們最有影響力的論文,

  • We're looking at what we call "academic age."

    之後就開始下滑。

  • Your academic age starts when you publish your first papers.

    下滑的速度很快,我大約——

  • I know some of you are still babies.

    我現在正在我職涯的三十年,

  • (Laughter)

    我有可能出版一篇 比我以前所有論文

  • So let's look at the probability

    都更有影響力的論文的機率,

  • that you publish your highest-impact paper.

    低於 1%。

  • And what you see is, indeed, the genius research is right.

    根據這些資料,我現在 就處在職涯的那個階段。

  • Most scientists tend to publish their highest-impact paper

    但有個問題。

  • in the first 10, 15 years in their career,

    我們沒有把控制做好。

  • and it tanks after that.

    控制指的是,

  • It tanks so fast that I'm about -- I'm exactly 30 years into my career,

    對科學做出隨機貢獻的科學家 看起來會是什麼樣子的?

  • and the chance that I will publish a paper that would have a higher impact

    或,那位科學家的產能會是什麼?

  • than anything that I did before

    他們何時撰寫論文?

  • is less than one percent.

    所以我們測量了產能,

  • I am in that stage of my career, according to this data.

    很驚人的是,產能,

  • But there's a problem with that.

    你在職涯第一、十、二十年 寫一篇論文的可能性,

  • We're not doing controls properly.

    很接近在你職涯的那個部分

  • So the control would be,

    有所影響的可能性。

  • what would a scientist look like who makes random contribution to science?

    長話短說,