Naomi Oreskes: Why we should trust scientists

譯者: William Choi 審譯者: Bighead Ge

Every day we face issues like climate change

每天我們要面對各種各樣的問題，

or the safety of vaccines

例如氣候變遷、疫苗安全等，

where we have to answer questions whose answers

我們必須回答這些問題，

rely heavily on scientific information.

而答案很大程度上依賴於科學資訊，

Scientists tell us that the world is warming.

科學家告訴我們世界正在暖化，

Scientists tell us that vaccines are safe.

科學家告訴我們疫苗是安全，

But how do we know if they are right?

但我們怎麼知道他們是對的？

Why should be believe the science?

為什麼我們要相信科學？

The fact is, many of us actually don't believe the science.

事實上，很多人並不相信科學。

Public opinion polls consistently show

民意調查一直顯示，

that significant proportions of the American people

大部分美國民眾

don't believe the climate is warming due to human activities,

並不相信氣候暖化是 人為活動造成的，

don't think that there is evolution by natural selection,

也不認為有物競天擇這回事，

and aren't persuaded by the safety of vaccines.

也不相信疫苗的安全。

So why should we believe the science?

那麼，為何我們應該相信科學？

Well, scientists don't like talking about science as a matter of belief.

科學家不喜歡把科學 說成是需要「相信」的事。

In fact, they would contrast science with faith,

說實話，他們認為 「科學」和「信仰」是相斥的，

and they would say belief is the domain of faith.

他們說「教義」只屬於 「信仰」的一部份，

And faith is a separate thing apart and distinct from science.

而「信仰」和「科學」 兩者本是風馬牛不相及。

Indeed they would say religion is based on faith

他們甚至說宗教以信仰為基礎，

or maybe the calculus of Pascal's wager.

或者像帕斯卡的賭注：

Blaise Pascal was a 17th-century mathematician

布萊茲．帕斯卡是 17 世紀的數學家，

who tried to bring scientific reasoning to the question of

他要把科學辯證帶入討論

whether or not he should believe in God,

應否相信上帝的存在。

and his wager went like this:

他打的賭是這樣：

Well, if God doesn't exist

嗯，如果上帝不存在，

but I decide to believe in him

但我決定相信上帝的存在，

nothing much is really lost.

那我真的沒太大損失，

Maybe a few hours on Sunday.

（可能損失了禮拜天的幾小時。）

(Laughter)

（笑聲）

But if he does exist and I don't believe in him,

然而，如果上帝真的存在， 而我沒有相信上帝，

then I'm in deep trouble.

那我就大遭殃啦。

And so Pascal said, we'd better believe in God.

所以帕斯卡說， 我們最好還是相信上帝吧。

Or as one of my college professors said,

或者，如同我其中一個 的大學教授說：

"He clutched for the handrail of faith."

「他抓著信念不放，

He made that leap of faith

視為天降神跡，

leaving science and rationalism behind.

把科學或理性思考遺忘掉。」

Now the fact is though, for most of us,

現在事實卻是，

most scientific claims are a leap of faith.

對很多人來說，很多科學主張 也沒有實驗基礎。

We can't really judge scientific claims for ourselves in most cases.

我們也很難判斷某些科學主張，

And indeed this is actually true for most scientists as well

甚至很多科學家也未能判斷

outside of their own specialties.

超出其專長領域的主張。

So if you think about it, a geologist can't tell you

所以你想一想， 地質學家就無法告訴你

whether a vaccine is safe.

疫苗到底是否安全。

Most chemists are not experts in evolutionary theory.

大多數化學家也不是 演化理論的專家。

A physicist cannot tell you,

一個物理學家也無法跟你說，

despite the claims of some of them,

儘管某些人有自己的主見，

whether or not tobacco causes cancer.

吸煙到底會否致癌。

So, if even scientists themselves

所以，即使科學家

have to make a leap of faith

在超出自己的專長領域外，

outside their own fields,

都只相信天降神跡，

then why do they accept the claims of other scientists?

那樣他們為什麼接受 其他科學家所提出的科學主張呢？

Why do they believe each other's claims?

那樣他們為什麼 接受其他人的主張呢？

And should we believe those claims?

那樣我們應該相信他們的主張嗎？

So what I'd like to argue is yes, we should,

所以我認為，是的， 我們應該相信，

but not for the reason that most of us think.

但不是大部分人想的原因。

Most of us were taught in school that the reason we should

大部分人在學校接受教育，

我們應該相信科學， 原因是其科學方法。

believe in science is because of the scientific method.

We were taught that scientists follow a method

老師說科學家遵循一套方法，

and that this method guarantees

而這套方法

the truth of their claims.

確保理論正確。

The method that most of us were taught in school,

大部份人在學校裡 學習的那套方法，

we can call it the textbook method,

我們稱之為課本上的方法，

is the hypothetical deductive method.

就是「假說演繹法」。

According to the standard model, the textbook model,

根據標準的模式， 教科書教材的模式，

scientists develop hypotheses, they deduce

科學家們提出假說，

the consequences of those hypotheses,

推論那些假說的結果，

and then they go out into the world and they say,

然後他們到現實世界去驗證，

"Okay, well are those consequences true?"

「好，結果是否如我所料？」

Can we observe them taking place in the natural world?

我們可否在自然界中 觀察到這樣的結果嗎？

And if they are true, then the scientists say,

如果可以，科學家就會說，

"Great, we know the hypothesis is correct."

「太棒了，我們知道假說是正確的。」

So there are many famous examples in the history

科學史上有很多著名的例子，

of science of scientists doing exactly this.

科學家就是這樣做的。

One of the most famous examples

其中一個有名的例子

comes from the work of Albert Einstein.

來自愛因斯坦的理論。

When Einstein developed the theory of general relativity,

當愛因斯坦提出廣義相對論時，

one of the consequences of his theory

他的其中一個論點是，

was that space-time wasn't just an empty void

空間和時間不是空洞，沒有實體的，

but that it actually had a fabric.

事實上其結構為纖維交織似的，

And that that fabric was bent

而且在質量很大的物體面前， 例如太陽，

in the presence of massive objects like the sun.

時空就會被扭曲。

So if this theory were true then it meant that light

那麼假設這個論點是正確的，

as it passed the sun

意味着當光線穿越太陽時，

should actually be bent around it.

就會圍繞著太陽而扭曲。

That was a pretty startling prediction

那是一個很驚人的預測，

and it took a few years before scientists

而科學家要到好多年後，

were able to test it

才能夠去檢驗理論。

but they did test it in 1919,

他們在1919年進行測試，

and lo and behold it turned out to be true.

真怪呀，結果證明是真的：

Starlight actually does bend as it travels around the sun.

星光行經太陽時， 確實發生彎曲。

This was a huge confirmation of the theory.

這對相對論是很重大的確證，

It was considered proof of the truth

它被認為對這個全新想法　

of this radical new idea,

提供真實證明，

and it was written up in many newspapers

全球各大報社也爭相報導。

around the globe.

全球各大報社也爭相報導。

Now, sometimes this theory or this model

現在，這個理論或模式

is referred to as the deductive-nomological model,

有時候被稱作「演繹－律則」模式，

mainly because academics like to make things complicated.

主要的原因是 學術界喜歡把事情搞得很複雜，

But also because in the ideal case, it's about laws.

而且在理想情況下， 這跟「定律」有關。

So nomological means having to do with laws.

「律則」就必定跟「定律」有關。

And in the ideal case, the hypothesis isn't just an idea:

在理想的情況下， 假說不僅是一種想法：

ideally, it is a law of nature.

這是自然界的定律。

Why does it matter that it is a law of nature?

自然界定律為什麼重要？

Because if it is a law, it can't be broken.

因為定律不能被打破。

If it's a law then it will always be true

如果它是定律，就永遠都是正確的，

in all times and all places

無論何時何地，

no matter what the circumstances are.

在任何情況下都是正確的。

And all of you know of at least one example of a famous law:

你們所有人都知道 至少一個著名定律的例子：

Einstein's famous equation, E=MC2,

愛因斯坦的著名方程式： E 等於 MC 平方。

which tells us what the relationship is

告訴我們能量與質量的關係，

between energy and mass.

告訴我們能量與質量的關係，

And that relationship is true no matter what.

而那個關係無論如何都是正確的。

Now, it turns out, though, that there are several problems with this model.

但是，我們後來發現 一些有關這個模式的問題，

The main problem is that it's wrong.

主要的問題是，它是錯的。

It's just not true. (Laughter)

這並不是正確的。（笑聲）

And I'm going to talk about three reasons why it's wrong.

我要舉出三個原因， 說明它為何是錯。

So the first reason is a logical reason.

第一個是邏輯上的原因，

It's the problem of the fallacy of affirming the consequent.

這是有關肯定後件謬誤的問題， (affirming the consequent)

So that's another fancy, academic way of saying

那是另一個異想天開的、 學術上的說法，

that false theories can make true predictions.

就是錯誤的理論 也可得到正確的預測結果，

So just because the prediction comes true

所以即使預測正確，

doesn't actually logically prove that the theory is correct.

邏輯上也未能證明 理論是正確的。

And I have a good example of that too, again from the history of science.

我可以再舉一個 科學史上很好的例子，

This is a picture of the Ptolemaic universe

這是一張托勒密宇宙的圖片，

with the Earth at the center of the universe

地球處於宇宙的中心，

and the sun and the planets going around it.

而太陽及其他行星圍繞著地球運轉。

The Ptolemaic model was believed

很多聰明人都相信 托勒密宇宙模型，

by many very smart people for many centuries.

已有幾個世紀了。

Well, why?

嗯，為什麼呢？

Well the answer is because it made lots of predictions that came true.

答案是，因為很多預測結果 的確符合現實狀況。

The Ptolemaic system enabled astronomers

天文學家根據托勒密系統，

to make accurate predictions of the motions of the planet,

精確預測行星運動，

in fact more accurate predictions at first

事實上較哥白尼的理論 都要精準很多，

than the Copernican theory which we now would say is true.

但是我們現在都知道 哥白尼的理論才正確。

So that's one problem with the textbook model.

這就是教科書教材模式的問題。

A second problem is a practical problem,

第二個問題是實務問題，

and it's the problem of auxiliary hypotheses.

跟輔助性假說有關。

Auxiliary hypotheses are assumptions

輔助性假說是科學家提出假設，

that scientists are making

有時候他們甚至不會發現 自己提出了假設，

that they may or may not even be aware that they're making.

So an important example of this

一個重要的例子就來自

comes from the Copernican model,

哥白尼的模型，

which ultimately replaced the Ptolemaic system.

而最終它取代托勒密系統，

So when Nicolaus Copernicus said,

當尼古拉．哥白尼說，

actually the Earth is not the center of the universe,

地球實際上不是宇宙的中心，

the sun is the center of the solar system,

太陽才是太陽系的中心，

the Earth moves around the sun.

地球是繞著太陽運轉。

Scientists said, well okay, Nicolaus, if that's true

科學家們說：好啊，尼古拉， 如果你說的是真的，

we ought to be able to detect the motion

那我們應該感覺得到 地球在移動，

of the Earth around the sun.

繞著太陽跑。

And so this slide here illustrates a concept

這張投影片展示出

known as stellar parallax.

恆星視差的概念。

And astronomers said, if the Earth is moving

天文學家說：如果地球正在移動，

and we look at a prominent star, let's say, Sirius --

那麼我們觀察一顆明亮的星星時， 譬如說天狼星，

well I know I'm in Manhattan so you guys can't see the stars,

嗯，我知道在曼哈頓， 你們是看不到星星的，

but imagine you're out in the country, imagine you chose that rural life —

但想像一下，你們到鄉村， 選擇過著農村生活，

and we look at a star in December, we see that star

我們在十二月的時候看星，

against the backdrop of distant stars.

就看到遙遠恆星的背景 襯托着天狼星，

If we now make the same observation six months later

如果我們六個月後 再做同樣的觀測，

when the Earth has moved to this position in June,

在6月時，當地球已轉到這個位置，

we look at that same star and we see it against a different backdrop.

我們在不同的背景下， 看著同一顆星，

That difference, that angular difference, is the stellar parallax.

那種差異，那種角度的差異，　　　 就是恆星視差（斗轉星移）。

So this is a prediction that the Copernican model makes.

所以這是根據哥白尼理論 所作的預測，

Astronomers looked for the stellar parallax

天文學家觀測尋找恆星視差，

and they found nothing, nothing at all.

但就沒有觀測到，沒有發現。

And many people argued that this proved that the Copernican model was false.

因此很多人認為 這證明哥白尼的模型是錯的。

So what happened?

所以這是怎麼回事？

Well, in hindsight we can say that astronomers were making

嗯，事後看來，我們可以說，

天文學家作出兩個輔助性假說，

two auxiliary hypotheses, both of which

我們現在都知道兩者並不正確。

we would now say were incorrect.

The first was an assumption about the size of the Earth's orbit.

第一個是有關「地球運行軌道」 大小的假設。

Astronomers were assuming that the Earth's orbit was large

天文學家假設地球的軌道

relative to the distance to the stars.

遠大於跟恆星的距離。

Today we would draw the picture more like this,

今天我們畫出來的圖 比較像這樣：

this comes from NASA,

這幅來自美國太空總署，

and you see the Earth's orbit is actually quite small.

你們可以看到地球的軌道 事實上相當地小，

In fact, it's actually much smaller even than shown here.

其實較這張圖畫還要小，

The stellar parallax therefore,

因此，恆星視差非常小，

is very small and actually very hard to detect.

很難偵測到的。

And that leads to the second reason

這也帶到第二個原因，

why the prediction didn't work,

為什麼沒有觀測到，

because scientists were also assuming

因為科學家也誤以為

that the telescopes they had were sensitive enough

當時的望遠鏡夠精密，

to detect the parallax.

足以偵測到視差。

And that turned out not to be true.

而最後發現這是錯的。

It wasn't until the 19th century

直到19世紀，

that scientists were able to detect

科學家才有辦法偵測到恆星視差。

the stellar parallax.

科學家才有辦法偵測到恆星視差。

So, there's a third problem as well.

所以，還有第三個問題。

The third problem is simply a factual problem,

第三個問題簡而言之 就是事實問題。

that a lot of science doesn't fit the textbook model.

有很多科學不符合教科書上的方法論，

A lot of science isn't deductive at all,

很多科學根本不是 推理演繹出來的，

it's actually inductive.

而是歸納出來的。

And by that we mean that scientists don't necessarily

意思是說，科學家不一定要

start with theories and hypotheses,

先建立理論假設，

often they just start with observations

他們常常只是從觀察出發，

of stuff going on in the world.

觀察世上萬物的運行。

And the most famous example of that is one of the most

最有名的例子查爾斯．達爾文， 也是世上最有名的科學家之一，

famous scientists who ever lived, Charles Darwin.

最有名的例子查爾斯．達爾文， 也是世上最有名的科學家之一，

When Darwin went out as a young man on the voyage of the Beagle,

達爾文年輕的時候 參與小獵犬號的航行，

he didn't have a hypothesis, he didn't have a theory.

他沒有假設，沒有理論，

He just knew that he wanted to have a career as a scientist

只知道要成為一位科學家，

and he started to collect data.

他開始蒐集資料。

Mainly he knew that he hated medicine

主要是他知道他不喜歡醫學，

because the sight of blood made him sick so

看到血會感到不舒服，

he had to have an alternative career path.

因此不得不選擇另一條路。

So he started collecting data.

所以他開始收集資料。

And he collected many things, including his famous finches.

他收集很多東西， 包括他最出名的雀鳥，

When he collected these finches, he threw them in a bag

他把收集的雀鳥丟到包裡，

and he had no idea what they meant.

他也不知道這有什麼意義。

Many years later back in London,

多年以後他回到倫敦，

Darwin looked at his data again and began

達爾文再把資料拿出來看，

to develop an explanation,

然後開始建立學說，

and that explanation was the theory of natural selection.

就是說明物競天擇的理論。

Besides inductive science,

除了歸納法，

scientists also often participate in modeling.

科學家們也常建立模型。

One of the things scientists want to do in life

科學家一生中的志業之一，

is to explain the causes of things.

就是解釋事物的緣由。

And how do we do that?

我們要怎麼做呢？

Well, one way you can do it is to build a model

嗯，一種方法是建立一個模型，

that tests an idea.

然後做測試，

So this is a picture of Henry Cadell,

這是一張亨利．卡道爾的照片，

who was a Scottish geologist in the 19th century.

他是 19 世紀的蘇格蘭地理學家。

You can tell he's Scottish because he's wearing

可以看出他是蘇格蘭人，

a deerstalker cap and Wellington boots.

因為他頭戴獵鹿帽，腳穿威靈頓長靴。

(Laughter)

〔觀眾笑〕

And Cadell wanted to answer the question,

卡道爾想要找出答案，

how are mountains formed?

山巒是如何形成的？

And one of the things he had observed

其中他觀察到一件事，

is that if you look at mountains like the Appalachians,

若看看像是 「阿帕拉契」這座山脈，

you often find that the rocks in them

你們常常會看到裡面的岩石

are folded,

有很多褶皺，

and they're folded in a particular way,

而且是一種特定的摺法，

which suggested to him

讓他覺得

that they were actually being compressed from the side.

它們像是從一邊被擠壓 而形成的褶皺。

And this idea would later play a major role

這個想法在後來的陸塊漂移 學說中，扮演了重要角色。

in discussions of continental drift.

這個想法在後來的陸塊漂移 學說中，扮演了重要角色。

So he built this model, this crazy contraption

所以他建了個模型， 瘋狂的玩意兒，

with levers and wood, and here's his wheelbarrow,

用撬棒、木頭、 這是他的單輪手推車、

buckets, a big sledgehammer.

一些桶子、一把大錘，

I don't know why he's got the Wellington boots.

不知為何他還穿著威靈頓靴...

Maybe it's going to rain.

也許那時快下雨了。

And he created this physical model in order

然後他就弄出了個實物模型，

to demonstrate that you could, in fact, create

來演示你真的可以 模擬出岩石的紋理，

patterns in rocks, or at least, in this case, in mud,

在這邊至少用了泥巴去模擬， 近似於山脈的狀況，

that looked a lot like mountains

在這邊至少用了泥巴去模擬， 近似於山脈的狀況，

if you compressed them from the side.

如果你從旁擠壓它的話。

So it was an argument about the cause of mountains.

所以這就是山脈成因的論據。

Nowadays, most scientists prefer to work inside,

這些年，大部分的科學家 比較喜歡在室內工作，

so they don't build physical models so much

所以他們比較少建實物模型，

as to make computer simulations.

而是用電腦模擬。

But a computer simulation is a kind of a model.

但電腦模擬也是一種模型，

It's a model that's made with mathematics,

以數學運算建立模型，

and like the physical models of the 19th century,

如同 19 世紀的實物模型，

it's very important for thinking about causes.

這是找出原因的重要手段。

So one of the big questions to do with climate change,

因此，要回答關於「氣候變遷」 這樣的大哉問，

we have tremendous amounts of evidence

我們有海量的證據，

that the Earth is warming up.

證明地球一直在暖化。

This slide here, the black line shows

這張投影片中，黑色曲線表示

the measurements that scientists have taken

科學家在過去150年以來的 量測數據。

for the last 150 years

科學家在過去150年以來的 量測數據。

showing that the Earth's temperature

顯示地球的溫度，

has steadily increased,

正穩定上升中。

and you can see in particular that in the last 50 years

你們也可以看到特別是 最近 50 年，

there's been this dramatic increase

則是大幅度的溫昇，

of nearly one degree centigrade,

幾乎是攝氏 1 度，

or almost two degrees Fahrenheit.

或換算約為華氏 2 度。

So what, though, is driving that change?

那所以，是什麼因素造成變遷？

How can we know what's causing

我們要如何了解暖化的成因？

the observed warming?

我們要如何了解暖化的成因？

Well, scientists can model it

嗯，科學家可以建立模型，

using a computer simulation.

利用電腦模擬運算。

So this diagram illustrates a computer simulation

這張圖顯示了電腦模擬結果，

that has looked at all the different factors

加入了所有我們想得到的

that we know can influence the Earth's climate,

可能會影響地球氣候的變因。

so sulfate particles from air pollution,

有來自空氣污染的硫酸鹽微粒，

volcanic dust from volcanic eruptions,

來自火山噴發的火山灰、

changes in solar radiation,

太陽輻射變化、

and, of course, greenhouse gases.

當然，還有溫室效應氣體。

And they asked the question,

而他們要問的是，

what set of variables put into a model

要引用哪些變數，放入此模型，

will reproduce what we actually see in real life?

可以模擬重現 我們看到的現實情形？

So here is the real life in black.

所以這裡的黑線表示現實狀況，

Here's the model in this light gray,

而淺灰色的則表示模擬結果。

and the answer is

答案是，

a model that includes, it's the answer E on that SAT,

學測試題常有的 選項「E」：以上皆是。

all of the above.

學測試題常有的 選項「E」：以上皆是。

The only way you can reproduce

要達到重現的唯一方法， 最接近實際量測溫度數據的，

the observed temperature measurements

要達到重現的唯一方法， 最接近實際量測溫度數據的，

is with all of these things put together,

就是把所有因素全都加入，

including greenhouse gases,

包括溫室氣體排放，

and in particular you can see that the increase

而你們可以特別注意到， 溫室氣體增加的趨勢，

而你們可以特別注意到， 溫室氣體增加的趨勢，

in greenhouse gases tracks

和 50 年來溫度的急遽變化， 有非常大的關聯。

this very dramatic increase in temperature

和 50 年來溫度的急遽變化， 有非常大的關聯。

over the last 50 years.

And so this is why climate scientists say

這就是為什麼氣候學家會說，

it's not just that we know that climate change is happening,

我們不只知道氣候正在改變，

we know that greenhouse gases are a major part

而且我們確知溫室氣體

是最主要的成因。

of the reason why.

So now because there all these different things

現在，因為科學家們 做各種不同的研究，

that scientists do,

現在，因為科學家們 做各種不同的研究，

the philosopher Paul Feyerabend famously said,

哲學家保羅．費耶阿本德 有句名言：

"The only principle in science

「科學持續進步的唯一原則，

that doesn't inhibit progress is: anything goes."

就是想方設法， 無所不用其極。」

Now this quotation has often been taken out of context,

這段話老是被斷章取義，

because Feyerabend was not actually saying

因為費耶阿本德其實不是在說，

that in science anything goes.

科學無所不用其極。

What he was saying was,

他要說的是，

actually the full quotation is,

其實他的原句是：

"If you press me to say

「如果非要問我

what is the method of science,

什麼是科學方法？

I would have to say: anything goes."

我只能說：想方設法， 無所不用其極。」

What he was trying to say

他想說的是，

is that scientists do a lot of different things.

科學家會想方設法，

Scientists are creative.

科學家要很有創意。

But then this pushes the question back:

但這又回到原來的問題：

If scientists don't use a single method,

如果科學沒有單一的方法，

then how do they decide

那他們怎麼決定

what's right and what's wrong?

何者正確，何者錯誤？

And who judges?

由誰來裁決呢？

And the answer is, scientists judge,

答案是，由科學家判斷，

and they judge by judging evidence.

他們以「證據」評判。

Scientists collect evidence in many different ways,

科學家用各種手法收集證據，

but however they collect it,

但不管用什麼方法收集，

they have to subject it to scrutiny.

他們都要接受審查。

And this led the sociologist Robert Merton

這就帶到社會學家 羅伯特．莫頓所說的，

to focus on this question of how scientists

問題應集中在科學家們是如何 審視資料及證據，

scrutinize data and evidence,

問題應集中在科學家們是如何 審視資料及證據，

and he said they do it in a way he called

他說，他們用的方式， 稱作「系統性懷疑」。

"organized skepticism."

他說，他們用的方式， 稱作「系統性懷疑」。

And by that he meant it's organized

他意思是說，有系統，

because they do it collectively,

因為他們採用系統組織方式， 他們有集體性；

they do it as a group,

因為他們採用系統組織方式， 他們有集體性；

and skepticism, because they do it from a position

而懷疑，是由於他們以 不輕信為出發點。

of distrust.

而懷疑，是由於他們以 不輕信為出發點。

That is to say, the burden of proof

也就是說，提出新主張的人 必須負責證明他的理論。

is on the person with a novel claim.

也就是說，提出新主張的人 必須負責證明他的理論。

And in this sense, science is intrinsically conservative.

此即意謂著， 科學的本質是保守的。

It's quite hard to persuade the scientific community

要說服科學界是非常困難的，

to say, "Yes, we know something, this is true."

他們很難輕易說出： 「是，我們確信此事為真。」

So despite the popularity of the concept

姑且不論大家擁戴 「突破性思維」這個概念，

of paradigm shifts,

姑且不論大家擁戴 「典範轉移」這個概念，

what we find is that actually,

我們發現事實上，

really major changes in scientific thinking

在科學史上，科學的思考模式， 也很少有所改變。

are relatively rare in the history of science.

在科學史上，科學的思考模式， 很少有所改變。

So finally that brings us to one more idea:

所以最後， 這又給我們帶來另一個想法，

If scientists judge evidence collectively,

若科學家集體評判證據，

this has led historians to focus on the question

這導引歷史學家 集中至一件事：共識。

of consensus,

這導引歷史學家 集中至一件事：共識。

and to say that at the end of the day,

到頭來我們說：

what science is,

何謂科學？

what scientific knowledge is,

何謂科學知識？

is the consensus of the scientific experts

其實就是科學專家們的共識。

who through this process of organized scrutiny,

他們通過組織性的審查過程，

collective scrutiny,

集體審核，

have judged the evidence

對證據做出評判，

and come to a conclusion about it,

並得出結論， 不論贊成、反對皆然。

either yea or nay.

並得出結論， 不論贊成、反對皆然。

So we can think of scientific knowledge

所以我們可以將科學知識 視為一種專家共識。

as a consensus of experts.

所以我們可以將科學知識 視為一種專家共識。

We can also think of science as being

我們也可以把科學看作

a kind of a jury,

一種陪審制度，

except it's a very special kind of jury.

儘管這是種很特殊的陪審制度。

It's not a jury of your peers,

陪審員不是人人可當，

it's a jury of geeks.

而是由科學宅宅們擔任。

It's a jury of men and women with Ph.D.s,

陪審員有男有女， 全都是博士。

and unlike a conventional jury,

和傳統的陪審團有所不同，

which has only two choices,

傳統只有兩種選擇，

guilty or not guilty,

有罪，或無罪，

the scientific jury actually has a number of choices.

科學界的陪審團 其實有多種選擇。

Scientists can say yes, something's true.

科學家可以說： 對，某件事是真的。

Scientists can say no, it's false.

科學家可以說： 不，這件事不正確。

Or, they can say, well it might be true

或他們也可說： 嗯，這可能是對的，

but we need to work more and collect more evidence.

可是我們需要再多花些功夫， 收集更多證據。

Or, they can say it might be true,

或者，他們會說： 這可能是對的，

but we don't know how to answer the question

但我們不知道如何找出 問題的答案，

and we're going to put it aside

所以我們先把問題放一邊，

and maybe we'll come back to it later.

晚點再回頭來想。

That's what scientists call "intractable."

科學家們把這叫做「懸而未決」。

But this leads us to one final problem:

而這又把我們帶到最後的問題：

If science is what scientists say it is,

如果科學是由科學家們說了算，

then isn't that just an appeal to authority?

那這不會被權威者把持嗎？

And weren't we all taught in school

我們在學校不是被教說： 服從權威是一種邏輯謬誤嗎？

that the appeal to authority is a logical fallacy?

我們在學校不是被教說： 服從權威是一種邏輯謬誤嗎？

Well, here's the paradox of modern science,

嗯，這是現代科學的弔詭之處。

the paradox of the conclusion I think historians

這種弔詭我想就是歷史學家、

and philosophers and sociologists have come to,

哲學家，和社會學家們 得到的結論，

that actually science is the appeal to authority,

其實科學是由權威者把持的，

but it's not the authority of the individual,

然而此權威非單一個人，

no matter how smart that individual is,

不論單一個人有多聰明，

like Plato or Socrates or Einstein.

像是柏拉圖、 或蘇格拉底，或愛因斯坦，

It's the authority of the collective community.

這是整體學界的權威性，

You can think of it is a kind of wisdom of the crowd,

你可以把它想成群眾的智慧，

but a very special kind of crowd.

但是是很特殊的一群人，

Science does appeal to authority,

科學的確來自權威，

but it's not based on any individual,

但並非基於服從任何個人，

no matter how smart that individual may be.

不論他有多麼地聰明；

It's based on the collective wisdom,

它是基於集體智慧，

the collective knowledge, the collective work,

群體的智識， 群體的工作，

of all of the scientists who have worked

每位科學家一直鑽研的

on a particular problem.

某個特定問題。

Scientists have a kind of culture of collective distrust,

科學家有一種共通的 集體懷疑性，

this "show me" culture,

是「眼見為憑」的文化，

illustrated by this nice woman here

由這位優秀女性為我們呈現，

showing her colleagues her evidence.

把證據展示給她的同事看。

Of course, these people don't really look like scientists,

當然，這些人 看起來不太像科學家，

because they're much too happy.

因為他們好像太歡樂了...

(Laughter)

〔觀眾笑〕

Okay, so that brings me to my final point.

好，所以它帶到了我的終點：

Most of us get up in the morning.

我們大部分人 早上起床，

Most of us trust our cars.

我們大部分人 都相信我們的車子，

Well, see, now I'm thinking, I'm in Manhattan,

（現在想想，我們身處曼哈頓， 這個例子有點爛...）

this is a bad analogy,

but most Americans who don't live in Manhattan

但是大部分的美國人， 不住在曼哈頓的那些人，

get up in the morning and get in their cars

早上醒來，去開車，

and turn on that ignition, and their cars work,

插上鑰匙發動，車子啟動了，

and they work incredibly well.

一切非常順利。

The modern automobile hardly ever breaks down.

現代的汽車很少壞掉，

So why is that? Why do cars work so well?

為什麼呢？為什麼車子這麼乖？

It's not because of the genius of Henry Ford

這不是因為亨利．福特是天才，

or Karl Benz or even Elon Musk.

也不是因為卡爾．賓士 或甚至伊隆．馬斯克的天份。

It's because the modern automobile

這是因為現代的汽車， 是發展了超過100年的產品，

is the product of more than 100 years of work

這是因為現代的汽車， 是發展了超過100年的產品，

這心血結晶，來自 數以百計、成千上萬的人們。

by hundreds and thousands

and tens of thousands of people.

這心血結晶，來自 數以百計、成千上萬的人們。

The modern automobile is the product

這樣的現代產品，

of the collected work and wisdom and experience

是集群眾智慧與經驗於一身，

of every man and woman who has ever worked

每位男性和女性投注心思， 在研發汽車，

on a car,

每位男性和女性投注心思， 在研發汽車，

and the reliability of the technology is the result

其所達成的技術可靠度，

of that accumulated effort.

即是來自於群體累積的成果。

We benefit not just from the genius of Benz

我們不僅是受惠於 賓士、福特、馬斯克的天份。

and Ford and Musk

我們不僅是受惠於 賓士、福特、馬斯克的天份。

but from the collective intelligence and hard work

而是群體的智識、嘔心瀝血，

of all of the people who have worked

每位在現今汽車業界工作過的人 都有所貢獻。

on the modern car.

每位在現今汽車業界工作過的人 都有所貢獻。

And the same is true of science,

科學也是如此， 只是發展的歷史還更長一些。

only science is even older.

科學也是如此， 只是發展的歷史還更長一些。

Our basis for trust in science is actually the same

我們對於科學和技術的信任 基礎是一樣的，

as our basis in trust in technology,

我們對於科學和技術的信任 基礎是一樣的，

and the same as our basis for trust in anything,

對任何事物的信任 也基於相同一件事，

namely, experience.

亦即：經驗。

But it shouldn't be blind trust

然而這不應是盲目的信任， 科學之於任何事物皆然。

any more than we would have blind trust in anything.

然而這不應是盲目的信任， 科學之於任何事物皆然。

Our trust in science, like science itself,

我們對科學的信任， 就如同科學本身，

should be based on evidence,

應該要基於證據，

and that means that scientists

這意味著科學家們

have to become better communicators.

必須成為更好的溝通者。

They have to explain to us not just what they know

不僅要向我們說明 他們已知的事情，

but how they know it,

也要說明是如何得知的，

and it means that we have to become better listeners.

而這也表示「我們」 必須要成為更好的聽眾。

Thank you very much.

謝謝各位。

(Applause)

(掌聲)