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  • There is an ancient proverb that says

    有句古老的諺語這麼說:

  • it's very difficult to find a black cat in a dark room,

    「在一片漆黑的房間裡,是很難找出一隻黑貓的,

  • especially when there is no cat.

    特別當房間裡根本沒有貓的時候。」

  • I find this a particularly apt description of science

    我覺得將這句話用來形容科學

  • and how science works --

    和科學運作的方式,是非常貼切的。

  • bumbling around in a dark room, bumping into things,

    科學探索就像在漆黑的房間裡亂竄, 然後撞到了某些東西,

  • trying to figure out what shape this might be,

    試圖了解這個東西是什麼形態,

  • what that might be,

    那個東西又可能是什麼。

  • there are reports of a cat somewhere around,

    有報告說一隻貓就在附近,

  • they may not be reliable, they may be,

    這消息可能不是真的,也可能是真的,

  • and so forth and so on.

    就這樣反反覆覆。

  • Now I know this is different than the way most people

    這樣的說法跟大多數人

  • think about science.

    對科學的印象不一樣。

  • Science, we generally are told,

    一般我們對「科學」的理解,

  • is a very well-ordered mechanism for

    就是一套高度秩序化的機制,

  • understanding the world,

    用以解釋世界的種種現象,

  • for gaining facts, for gaining data,

    得到事實和數據。

  • that it's rule-based,

    一切都有規則,

  • that scientists use this thing called the scientific method

    科學家們運用「科學方法」做研究,

  • and we've been doing this for 14 generations or so now,

    至今已有約14代人 (420年),

  • and the scientific method is a set of rules

    而「科學方法」就是「一套規則,

  • for getting hard, cold facts out of the data.

    用來從數據中得到客觀確鑿的事實。」

  • I'd like to tell you that's not the case.

    這裡我告訴大家,並不是這麼回事。

  • So there's the scientific method,

    「科學方法」是存在的,

  • but what's really going on is this. (Laughter)

    但實際發生的事情是…...(笑聲)

  • [The Scientific Method vs. Farting Around]

    [科學方法 vs 狗屁瞎扯]

  • And it's going on kind of like that.

    實際的狀況大概像這樣:

  • [... in the dark] (Laughter)

    [.....在黑暗中放狗屁](笑聲)

  • So what is the difference, then,

    所以,差別在哪裡呢?

  • between the way I believe science is pursued

    我所相信的科學真諦,

  • and the way it seems to be perceived?

    為何與科學在人們心目中的印象如此不同?

  • So this difference first came to me in some ways

    我第一次意識到兩者的差異,

  • in my dual role at Columbia University,

    是在哥倫比亞大學身兼兩職的時候。

  • where I'm both a professor and run a laboratory in neuroscience

    我當時既當教授, 也主持神經科學的實驗室研究,

  • where we try to figure out how the brain works.

    研究目的是找出腦部運作的原理。

  • We do this by studying the sense of smell,

    我們的實驗室以研究氣味感知

  • the sense of olfaction, and in the laboratory,

    和人類嗅覺為切入點。在實驗室,

  • it's a great pleasure and fascinating work

    這可是非常吸引人而有趣的工作,

  • and exciting to work with graduate students and post-docs

    我很高興能與那些 碩士研究生和博士後共事,

  • and think up cool experiments to understand how this

    一起設計有趣的實驗方法 來去瞭解嗅覺如何運作,

  • sense of smell works and how the brain might be working,

    以及去瞭解大腦相應地如何運作。

  • and, well, frankly, it's kind of exhilarating.

    老實說,這项研究相當振奮我心。

  • But at the same time, it's my responsibility

    但同時我也身兼教職,

  • to teach a large course to undergraduates on the brain,

    我要教本科生關於腦科學的一門大課,

  • and that's a big subject,

    這可是個大工程,

  • and it takes quite a while to organize that,

    我花了很多工夫設計課程內容,

  • and it's quite challenging and it's quite interesting,

    是個很有挑戰性也很有趣的工作。

  • but I have to say, it's not so exhilarating.

    但我得說,設計課程並沒有為我帶來振奮感。

  • So what was the difference?

    為什麼呢?差別在哪?

  • Well, the course I was and am teaching

    那時到現在我一直在教的這門課,

  • is called Cellular and Molecular Neuroscience - I. (Laughs)

    叫做「細胞和分子神經學」——壹。(笑聲)

  • It's 25 lectures full of all sorts of facts,

    25堂課,介紹各種研究結果,

  • it uses this giant book called "Principles of Neural Science"

    教材是這本鴻篇巨制:「神經科學原理」,

  • by three famous neuroscientists.

    由三位著名的神經科學家共同編撰。

  • This book comes in at 1,414 pages,

    全書共1414頁,

  • it weighs a hefty seven and a half pounds.

    重達7.6英磅,

  • Just to put that in some perspective,

    給大家一個概念,

  • that's the weight of two normal human brains.

    這本書的重量相當於兩個正常人類的大腦。

  • (Laughter)

    (笑聲)

  • So I began to realize, by the end of this course,

    於是我開始意識到, 當學生們修完了這門課,

  • that the students maybe were getting the idea

    他們也許會認為,

  • that we must know everything there is to know about the brain.

    要瞭解大腦, 得先把現有知識全吸收盡才行。

  • That's clearly not true.

    這想法顯然是不對的。

  • And they must also have this idea, I suppose,

    我猜他們一定也有這個想法,

  • that what scientists do is collect data and collect facts

    科學家的工作就只是收集數據和事實,

  • and stick them in these big books.

    再訂到這樣的厚重教科書裡。

  • And that's not really the case either.

    這同樣也不是事實。

  • When I go to a meeting, after the meeting day is over

    我去參加研討會,會議結束之後,

  • and we collect in the bar over a couple of beers with my colleagues,

    我和同事們一起 聚在酒吧裡喝上幾瓶啤酒,

  • we never talk about what we know.

    我們談論的話題, 從來就不是已知的研究成果,

  • We talk about what we don't know.

    而是那些我們還不知道的東西。

  • We talk about what still has to get done,

    我們討論還有什麼問題需要研究,

  • what's so critical to get done in the lab.

    什麼是實驗室下一步的重點工作。

  • Indeed, this was, I think, best said by Marie Curie

    事實上,我認為,居里夫人給出了最好的詮釋:

  • who said that one never notices what has been done

    「不應該只著眼於自己完成了什麼,

  • but only what remains to be done.

    而應該看到還有什麼需要完成。」

  • This was in a letter to her brother after obtaining

    這句話出自居里夫人寫給哥哥的信中,

  • her second graduate degree, I should say.

    那時她剛拿到第二個碩士學位。

  • I have to point out this has always been one of my favorite pictures of Marie Curie,

    我要指出,這一直是 我最喜愛的居里夫人的照片之一。

  • because I am convinced that that glow behind her

    原因是,我確信她身後的光芒

  • is not a photographic effect. (Laughter)

    不是電腦特效。(笑聲)

  • That's the real thing.

    那一定是真的在發光。

  • It is true that her papers are, to this day,

    居里夫人的手稿,直到現在都

  • stored in a basement room in the Bibliothèque Française

    還保存在法國國家圖書館的地下貯藏室裡。

  • in a concrete room that's lead-lined,

    貯藏室的牆壁以水泥砌成, 中間埋鉛以防輻射。

  • and if you're a scholar and you want access to these notebooks,

    如果你以學者的身份申請查閱這些筆記,

  • you have to put on a full radiation hazmat suit,

    就得先穿上全套的輻射防護服,

  • so it's pretty scary business.

    這是頗嚇人的過程。

  • Nonetheless, this is what I think we were leaving out

    不過,我認為她的精神恰恰是

  • of our courses

    我們的課程所欠缺的,

  • and leaving out of the interaction that we have

    也是我們這些科學家 在與大眾互動時所欠缺的,

  • with the public as scientists, the what-remains-to-be-done.

    即「還有什麼需要完成」。

  • This is the stuff that's exhilarating and interesting.

    這是令人振奮和有趣的東西。

  • It is, if you will, the ignorance.

    如果你願意,可以叫它「無知」。

  • That's what was missing.

    這就是我們目前欠缺的。

  • So I thought, well, maybe I should teach a course

    於是我想,或許我應該開一門課

  • on ignorance,

    來討論「無知」,

  • something I can finally excel at, perhaps, for example.

    或許,這才是我真正擅長的。

  • So I did start teaching this course on ignorance,

    於是我真的去開了這門討論「無知」的課,

  • and it's been quite interesting

    得到很有趣的結果。

  • and I'd like to tell you to go to the website.

    我架設了網站,大家可以去看看,

  • You can find all sorts of information there. It's wide open.

    你能在網站裡找到各式各樣的資訊, 它是完全開放的。

  • And it's been really quite an interesting time for me

    我很享受在網站上

  • to meet up with other scientists who come in and talk

    和其他科學家一起切磋

  • about what it is they don't know.

    討論這些未知的、等待探索的領域。

  • Now I use this word "ignorance," of course,

    當然,我現在使用「無知」這個詞,

  • to be at least in part intentionally provocative,

    聽起來好像有些惡意挑釁的意味,

  • because ignorance has a lot of bad connotations

    因為「無知」有很多負面意思,

  • and I clearly don't mean any of those.

    但它們都不是我的本意。

  • So I don't mean stupidity, I don't mean a callow indifference

    我指的不是愚笨,

  • to fact or reason or data.

    也並非是指冷漠看待事實、推理或數據。

  • The ignorant are clearly unenlightened, unaware,

    這種「無知」是未被啟蒙的,沒意識到的,

  • uninformed, and present company today excepted,

    不接收資訊,像今日大家認為的大公司

  • often occupy elected offices, it seems to me.

    裡頭坐滿我們選出的官員,我是這麼想的。

  • That's another story, perhaps.

    這大概又是另一個議題了。

  • I mean a different kind of ignorance.

    我所指的「無知」是另一種意義的無知。

  • I mean a kind of ignorance that's less pejorative,

    它不包含那麼多的負面意義,

  • a kind of ignorance that comes from a communal gap in our knowledge,

    而是說我們在知識上共同的差距,

  • something that's just not there to be known

    一些我們還沒有瞭解的東西,

  • or isn't known well enough yet or we can't make predictions from,

    或者瞭解得還不夠的東西, 或者我們無法預知的東西。

  • the kind of ignorance that's maybe best summed up

    用一言以蔽之,

  • in a statement by James Clerk Maxwell,

    這句話是詹姆士‧克拉克‧麥斯威爾說的,

  • perhaps the greatest physicist between Newton and Einstein,

    他大概是牛頓和愛因斯坦之間 最偉大的物理學家,

  • who said, "Thoroughly conscious ignorance

    他說過:「完全自覺自醒的無知

  • is the prelude to every real advance in science."

    是每一次科學的實質性進步的前奏。」

  • I think it's a wonderful idea:

    我認為他提出了很棒的看法:

  • thoroughly conscious ignorance.

    「完全自覺自醒的無知」

  • So that's the kind of ignorance that I want to talk about today,

    也是我今天要探討的「無知」。

  • but of course the first thing we have to clear up

    不過首先我們得弄清楚

  • is what are we going to do with all those facts?

    該如何對待現有的研究成果?

  • So it is true that science piles up at an alarming rate.

    各式各樣的科學研究成果 以驚人的速率被提出,

  • We all have this sense that science is this mountain of facts,

    讓我們覺得科學似乎 就等於這座研究成果堆成的高山。

  • this accumulation model of science, as many have called it,

    科學的這種積累模式,就象很多人說的,

  • and it seems impregnable, it seems impossible.

    它似乎堅不可摧,也似乎不可企及

  • How can you ever know all of this?

    一個人怎麼能完全瞭解這裡頭所有的知識?

  • And indeed, the scientific literature grows at an alarming rate.

    事實上,科學文獻在以驚人的速度增長。

  • In 2006, there were 1.3 million papers published.

    2006年發表的科學論文總計130萬篇,

  • There's about a two-and-a-half-percent yearly growth rate,

    年增長率約2.5%。

  • and so last year we saw over one and a half million papers being published.

    去年,我們看到有150萬篇論文發表,

  • Divide that by the number of minutes in a year,

    這個數值除以一年的總分鐘數,

  • and you wind up with three new papers per minute.

    意味著每分鐘就有三篇論文發表。

  • So I've been up here a little over 10 minutes,

    我站在這裡超過十分鐘了,

  • I've already lost three papers.

    已經錯過了三篇論文沒讀 (*講者計算有誤 他會錯過三十篇)

  • I have to get out of here actually. I have to go read.

    我得離開這裡,趕緊去讀那些論文呢。

  • So what do we do about this? Well, the fact is

    我們拿這些研究成果怎麼辦呢?事實上,

  • that what scientists do about it is a kind of a controlled neglect, if you will.

    科學家的工作也是 某種程度的控制下的忽視。

  • We just don't worry about it, in a way.

    可以說,我們根本不去操這份心。

  • The facts are important. You have to know a lot of stuff

    研究成果固然重要,你要知道很多東西,

  • to be a scientist. That's true.

    才能成為科學家,這點沒錯。

  • But knowing a lot of stuff doesn't make you a scientist.

    但知識淵博並不能使你成為科學家。

  • You need to know a lot of stuff to be a lawyer

    要作律師也得掌握很多知識,

  • or an accountant or an electrician or a carpenter.

    作會計師、電工、木匠亦然。

  • But in science, knowing a lot of stuff is not the point.

    在科學領域裡,知識淵博並不是重點。

  • Knowing a lot of stuff is there to help you get

    知道的多是為了讓你

  • to more ignorance.

    更好地去探索「無知」。

  • So knowledge is a big subject, but I would say

    我要說,知識是個重要的議題,

  • ignorance is a bigger one.

    但「無知」更為重要。

  • So this leads us to maybe think about, a little bit

    這或許能讓我們想到,多多少少

  • about, some of the models of science that we tend to use,

    想到一些常用來類比科學的模型。

  • and I'd like to disabuse you of some of them.

    我要糾正你們對這些模型的錯誤看法。

  • So one of them, a popular one, is that scientists

    當中一個很受歡迎的理論是,

  • are patiently putting the pieces of a puzzle together

    科學家們將一片片拼圖耐心組合,

  • to reveal some grand scheme or another.

    去揭示一個又一個重大的發現。

  • This is clearly not true. For one, with puzzles,

    這顯然不是那麼回事。首先,說到拼圖,

  • the manufacturer has guaranteed that there's a solution.

    廠家能保證你一定能做出完整的圖案。

  • We don't have any such guarantee.

    而我們對科學研究卻沒法打保票。

  • Indeed, there are many of us who aren't so sure about the manufacturer.

    事實上,我們中的很多人對廠家也不太有信心。

  • (Laughter)

    (笑聲)

  • So I think the puzzle model doesn't work.

    所以我認為拼圖模型是說不通的。

  • Another popular model is that science is busy unraveling things

    另一個受歡迎的模型是, 科學就是忙著解開層層謎題,

  • the way you unravel the peels of an onion.

    就像剝洋蔥一樣。

  • So peel by peel, you take away the layers of the onion

    一層接著一層,你剝開洋蔥的皮,

  • to get at some fundamental kernel of truth.

    最後得到核心真相。

  • I don't think that's the way it works either.

    我也不認為科學是這樣運作的。

  • Another one, a kind of popular one, is the iceberg idea,

    另一種理論,也蠻有名的,就是冰山模型:

  • that we only see the tip of the iceberg but underneath

    我們所見只是冰山一角,

  • is where most of the iceberg is hidden.

    水面之下隱藏的冰山才占絕大部分。

  • But all of these models are based on the idea of a large body of facts

    這些模型都基於同一個理念, 即存在一個龐大的知識體系,

  • that we can somehow or another get completed.

    我們能夠通過這樣那樣的方法使之完善。

  • We can chip away at this iceberg and figure out what it is,

    我們可以鏟開冰山,去研究它究竟是怎麼回事,

  • or we could just wait for it to melt, I suppose, these days,

    或者以現今的氣候,等它融化就好。

  • but one way or another we could get to the whole iceberg. Right?

    但不論如何我們都能看透冰山的全貌,對吧?

  • Or make it manageable. But I don't think that's the case.

    或讓它變得可控。但我不這麼認為。

  • I think what really happens in science

    我認為科學真正的模型

  • is a model more like the magic well,

    更接近一座魔法水井,

  • where no matter how many buckets you take out,

    不論你從井中打了多少桶水,

  • there's always another bucket of water to be had,

    都還能再打出一桶。

  • or my particularly favorite one,

    還有一個我特別鍾愛的模型,

  • with the effect and everything, the ripples on a pond.

    考慮到種種影響和元素,科學就像是池塘裡的漣漪。

  • So if you think of knowledge being this ever-expanding ripple on a pond,

    如果把知識比作池塘裡不斷漾開的漣漪,

  • the important thing to realize is that our ignorance,

    那麼重要的是要意識到我們的「無知」,

  • the circumference of this knowledge, also grows with knowledge.

    就像漣漪的圓周長一樣, 隨著知識的擴大而不斷擴展。

  • So the knowledge generates ignorance.

    知識產生「無知」。

  • This is really well said, I thought, by George Bernard Shaw.

    蕭伯納說過一句很棒的話,

  • This is actually part of a toast that he delivered

    他在慶祝愛因斯坦工作成績的晚宴上

  • to celebrate Einstein at a dinner celebrating Einstein's work,

    為愛因斯坦致祝酒詞,

  • in which he claims that science

    他認為,與其說科學在解決問題,

  • just creates more questions than it answers. ["Science is always wrong. It never solves a problem without creating 10 more."]

    不如說是在製造問題。 [科學總是錯的。每當解決了一個問題,它總是製造出十個新的問題。]

  • I find that kind of glorious, and I think he's precisely right,

    我覺得這真是至理名言了。 他說的一點沒錯。

  • plus it's a kind of job security.

    這也說明了我們永遠不會失業。

  • As it turns out, he kind of cribbed that

    後來發現,這可能是借鑒了

  • from the philosopher Immanuel Kant

    哲學家康德的理念。

  • who a hundred years earlier had come up with this idea

    早在一百年前, 康德就提出了「問題相生」的概念,

  • of question propagation, that every answer begets more questions.

    每個答案都會帶來更多的問題。

  • I love that term, "question propagation,"

    我喜歡「 問題相生」這個術語,

  • this idea of questions propagating out there.

    這個「問題會衍生問題」的概念。

  • So I'd say the model we want to take is not

    所以我要說,我們想採用的模型,並不是

  • that we start out kind of ignorant and we get some facts together

    要從無知開始,共同找到一些現象,

  • and then we gain knowledge.

    然後獲得獲得某種知識。

  • It's rather kind of the other way around, really.

    實際情況正好相反。

  • What do we use this knowledge for?

    現有的知識有什麼用?

  • What are we using this collection of facts for?

    至今收集到的事實有什麼用?

  • We're using it to make better ignorance,

    我們要用它們來得到更好的「無知」,

  • to come up with, if you will, higher-quality ignorance.

    得到「高品質的無知」。

  • Because, you know, there's low-quality ignorance

    因為有低品質的無知,

  • and there's high-quality ignorance. It's not all the same.

    相對也有高品質的,兩者並不相同。

  • Scientists argue about this all the time.

    科學家們總是為此爭論。

  • Sometimes we call them bull sessions.

    有時我們稱它為鬥牛大會,

  • Sometimes we call them grant proposals.

    有時我們稱它為申請研究基金。

  • But nonetheless, it's what the argument is about.

    無論是哪個,我們爭論的點都是相同的,

  • It's the ignorance. It's the what we don't know.

    那就是「無知」,什麼是我們不知道的,

  • It's what makes a good question.

    怎樣才是一個好問題。

  • So how do we think about these questions?

    我們又怎麼看待這些問題呢?

  • I'm going to show you a graph that shows up

    給大家看一張圖,

  • quite a bit on happy hour posters in various science departments.

    它經常被各個科學部門用來做聚會的海報。

  • This graph asks the relationship between what you know

    這個圖表探討「你知道什麼」和「你瞭解多少」

  • and how much you know about it.

    兩者之間的關係。

  • So what you know, you can know anywhere from nothing to everything, of course,

    「你知道什麼」,你可以從一無所知到無所不知;

  • and how much you know about it can be anywhere

    「你瞭解多少」,則可以從只瞭解一點點

  • from a little to a lot.

    到瞭解很多。

  • So let's put a point on the graph. There's an undergraduate.

    讓我們在這張圖表上畫一個點,這是一名大學生。

  • Doesn't know much but they have a lot of interest.

    瞭解程度不高,但有很多的興趣。

  • They're interested in almost everything.

    他們幾乎對什麼事都感興趣。

  • Now you look at a master's student, a little further along in their education,

    現在來看一個碩士生, 因為他受教育的時間更長,

  • and you see they know a bit more,

    所以他們瞭解程度更高,

  • but it's been narrowed somewhat.

    但知識面變窄了。

  • And finally you get your Ph.D., where it turns out

    接下來終於你拿到博士學位了,結果…