Naomi Oreskes: Why we should trust scientists

翻译人员: Sanqiang Xiao 校对人员: Bangyou Xiang

Every day we face issues like climate change

每天，我们都面对着像气候变化或

or the safety of vaccines

疫苗安全这样的问题，

where we have to answer questions whose answers

而对这些问题的解答

rely heavily on scientific information.

都仰仗于科学知识。

Scientists tell us that the world is warming.

科学家告诉我们世界正在变暖。

Scientists tell us that vaccines are safe.

科学家告诉我们疫苗是安全的。

But how do we know if they are right?

但我们怎么知道他们说的是对的呢？

Why should be believe the science?

为什么我们要相信科学呢？

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

事实是，我们中的大多数人 实际上不相信科学。

Public opinion polls consistently show

民意调查一贯表明，

that significant proportions of the American people

有相当一部分美国人

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

不相信气候正在变暖是由于人类活动，

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

不相信有自然选择的生物演化，

and aren't persuaded by the safety of vaccines.

并且不相信疫苗的安全性。

So why should we believe the science?

那么我们为什么要相信科学呢？

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

好吧，科学家并不喜欢把 科学当作一种信念来讨论。

In fact, they would contrast science with faith,

事实上，他们会把科学与信仰相对，

and they would say belief is the domain of faith.

并且会说信念是信仰的一部分。

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

而信仰是一个处在科学之外， 与其截然不同的东西。

Indeed they would say religion is based on faith

事实上他们会说宗教是基于信仰的，

or maybe the calculus of Pascal's wager.

或是基于帕斯卡赌注的演算。

Blaise Pascal was a 17th-century mathematician

布莱兹·帕斯卡是一位17世纪的数学家，

who tried to bring scientific reasoning to the question of

他试着将科学的论证引入

whether or not he should believe in God,

他是否该信仰上帝这一问题，

and his wager went like this:

他的赌注如下：

Well, if God doesn't exist

好吧，如果上帝不存在，

but I decide to believe in him

但我决定信仰他，

nothing much is really lost.

没有什么大的损失。

Maybe a few hours on Sunday.

也许只是周日要花掉几个小时。

(Laughter)

（众人笑。） （译注：基督教周日礼拜。）

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

但如果他存在但我不信仰他，

then I'm in deep trouble.

那我就有很大的麻烦了。

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

所以帕斯卡说我们最好相信上帝，

Or as one of my college professors said,

或者像我的一个大学教授所说，

"He clutched for the handrail of faith."

“他紧紧抓住了信仰的扶手。”

He made that leap of faith

帕斯卡最终选择了信仰，

leaving science and rationalism behind.

放下了科学与理性。

Now the fact is though, for most of us,

事实是对我们中的大多数人，

most scientific claims are a leap of faith.

大多数科学结论都是一种信仰。

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

在大多数时候， 我们并不能亲自验证科学结论。

And indeed this is actually true for most scientists as well

事实上在专业领域之外，

outside of their own specialties.

对于大多是科学家来说也是这样。

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

所以就算你想知道一个疫苗是否安全，

whether a vaccine is safe.

一个地质学家也不能告诉你答案。

Most chemists are not experts in evolutionary theory.

大多数化学家也不是进化论的专家。

A physicist cannot tell you,

一个物理学家不能告诉你，

despite the claims of some of them,

烟草是否致癌，

whether or not tobacco causes cancer.

尽管他们中的一些说自己能。

So, if even scientists themselves

所以，如果连科学家

have to make a leap of faith

在自己的专业领域之外

outside their own fields,

都得相信无法感知的结论，

then why do they accept the claims of other scientists?

那么这些科学家为什么要相信 其他科学家的断言呢？

Why do they believe each other's claims?

为什么他们要相信彼此的结论？

And should we believe those claims?

我们也应该相信这些结论吗？

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

所以我的答案是”没错，我们应该相信。“

but not for the reason that most of us think.

但不是由于我们大多数人所想的原因。

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

学校教诲我们大多数人

believe in science is because of the scientific method.

要相信科学是因为那些科学方法。

We were taught that scientists follow a method

我们了解到科学家是遵从某种方法，

and that this method guarantees

并且这个方法保证了

the truth of their claims.

他们结论的正确性。

The method that most of us were taught in school,

大多数人在学校学到的这种方法，

we can call it the textbook method,

我们称之为教科书方法，

is the hypothetical deductive method.

是一种假设性的演绎推理。

According to the standard model, the textbook model,

根据标准的模型，即教科书模型，

scientists develop hypotheses, they deduce

科学家发展了假说，

the consequences of those hypotheses,

并推理出这些假说的结果，

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

然后他们对全世界宣称，

"Okay, well are those consequences true?"

“好的，这些结果正确吗？”

Can we observe them taking place in the natural world?

我们能够观测到 它们在自然界中发生吗？

And if they are true, then the scientists say,

如果它们是正确的，那么科学家说，

"Great, we know the hypothesis is correct."

“好的，我们知道假设是正确的。”

So there are many famous examples in the history

所以历史上有许多著名的

of science of scientists doing exactly this.

关于科学家们做了这件事的例子。

One of the most famous examples

最著名的例子之一

comes from the work of Albert Einstein.

来自爱因斯坦的工作。

When Einstein developed the theory of general relativity,

当爱因斯坦发展他的广义相对论时，

one of the consequences of his theory

理论的一个结果是

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

时空并不是空空如也，

but that it actually had a fabric.

而是有一个网状结构。

And that that fabric was bent

那种结构会在大质量物体

in the presence of massive objects like the sun.

比如太阳的附近弯曲。

So if this theory were true then it meant that light

所以如果这个理论是正确的,

as it passed the sun

那么当光线经过太阳时，

should actually be bent around it.

会在太阳附近被弯曲。

That was a pretty startling prediction

这是一个很惊人的预测，

and it took a few years before scientists

科学家花了很多年

were able to test it

才验证了它，

but they did test it in 1919,

但是他们确实在1919年进行了验证，

and lo and behold it turned out to be true.

并且结果是正确的。

Starlight actually does bend as it travels around the sun.

星光确实在经过太阳附近时被弯曲。

This was a huge confirmation of the theory.

这是对广义相对论的一个重要肯定，

It was considered proof of the truth

这被认为是对广义相对论

of this radical new idea,

这一新颖理论的证明，

and it was written up in many newspapers

这次验证也被全球许多报纸

around the globe.

报道了。

Now, sometimes this theory or this model

有时候这些理论和模型

is referred to as the deductive-nomological model,

被称为演绎-规律模型（D-N模型），

mainly because academics like to make things complicated.

主要是因为学者喜欢让事情复杂化。

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

但也是因为在理想状态下，这是法则。

So nomological means having to do with laws.

Nomological表示要遵循法则。

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

在理想情况下，假说不仅仅是一个想法：

ideally, it is a law of nature.

它是自然法则。

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

为什么自然法则很重要呢？

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

因为法则不能被打破。

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

法则一定是正确的，

in all times and all places

不管何时何地，

no matter what the circumstances are.

不管在什么情况下。

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

你们大概都知道一个著名的法则：

Einstein's famous equation, E=MC2,

爱因斯坦的著名等式，E=mc^2，

which tells us what the relationship is

它告诉了我们能量和

between energy and mass.

质量的关系。

And that relationship is true no matter what.

这个关系在任何情况下都成立。

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

但结果表明， 似乎这个模型有一些问题。

The main problem is that it's wrong.

最主要的问题就是这个模型是错的。

It's just not true. (Laughter)

它不是正确的。 （笑声）

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

我想讲讲三个原因， 为什么说它是错的。

So the first reason is a logical reason.

第一个是逻辑问题。

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

问题在于荒谬地断定结果。

So that's another fancy, academic way of saying

这是另一种幻想，用学术术语称为

that false theories can make true predictions.

错误的理论得出正确的预测。

So just because the prediction comes true

所以仅仅因为预测是正确的，

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

并不能从逻辑上证明理论是正确的。

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

科学史上有一个很好的例子。

This is a picture of the Ptolemaic universe

这是一幅展现托勒密宇宙的图，

with the Earth at the center of the universe

地球在宇宙中心，

and the sun and the planets going around it.

太阳和行星都围绕它运行。

The Ptolemaic model was believed

托勒密模型在多个世纪中

by many very smart people for many centuries.

都被很多聪明人所接纳。

Well, why?

为什么？

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

因为由它进行的许多预测 都被证明是正确的。

The Ptolemaic system enabled astronomers

托勒密系统使得天文学家

to make accurate predictions of the motions of the planet,

对行星运行做出准确的预测，

in fact more accurate predictions at first

事实上甚至比哥白尼理论 在最初时更准确，

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

虽然后者现在被公认是正确的。

So that's one problem with the textbook model.

所以这是教科书模型的一个问题。

A second problem is a practical problem,

第二个问题是一个实际问题，

and it's the problem of auxiliary hypotheses.

问题在于辅助假说。

Auxiliary hypotheses are assumptions

辅助假说是科学家

that scientists are making

做出的假设，

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

他们可能甚至没意识到 自己做出了这个假设。

So an important example of this

一个很重要的例子是

comes from the Copernican model,

哥白尼模型，

which ultimately replaced the Ptolemaic system.

它最终取代了托勒密模型。

So when Nicolaus Copernicus said,

所以当尼古拉斯哥白尼宣称

actually the Earth is not the center of the universe,

事实上地球不是宇宙的中心，

the sun is the center of the solar system,

太阳是太阳系的中心，

the Earth moves around the sun.

地球围绕着太阳旋转，

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

科学家说，好吧，尼古拉斯， 如果这是对的，

we ought to be able to detect the motion

我们应该能检测出地球围绕

of the Earth around the sun.

太阳的运动。

And so this slide here illustrates a concept

这一页幻灯片展示了这个概念，

known as stellar parallax.

叫做星球视差。

And astronomers said, if the Earth is moving

天文家说，如果地球是运动的

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

我们关注一个显眼的星星， 比如天狼星——

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

在曼哈顿可能看不到这颗星星，

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

但想象你在乡村，你过着田园生活，

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

在十二月我们看着那个星星，

against the backdrop of distant stars.

以其他遥远的星星做背景。

If we now make the same observation six months later

而六个月之后， 如果我们做同样的观察，

when the Earth has moved to this position in June,

在六月，地球已经移动到了这个位置，

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

我们观察同样的星星 应该看到不同的背景。

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

这个视角的差异被称为星球视差。

So this is a prediction that the Copernican model makes.

这就是哥白尼模型做出的预测。

Astronomers looked for the stellar parallax

天文学家想找到星球视差，

and they found nothing, nothing at all.

但他们找不到任何差异。

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

许多人称这证明了哥白尼模型 是错误的。

So what happened?

怎么回事呢？

Well, in hindsight we can say that astronomers were making

事后我们能说天文学家

two auxiliary hypotheses, both of which

做出了两个假设，

we would now say were incorrect.

现在被公认都是错误的。

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

第一个是关于地球轨道大小的假设。

Astronomers were assuming that the Earth's orbit was large

天文学家假定地球的轨道很大，

relative to the distance to the stars.

相较于星星的距离。

Today we would draw the picture more like this,

今天我们会画出一个这样的图案

this comes from NASA,

来自NASA。

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

可以看到地球的轨道非常小。

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

事实上可能比这显示的更小。

The stellar parallax therefore,

因此，星球视差

is very small and actually very hard to detect.

会非常小，而且难以探测。

And that leads to the second reason

这也引出了另一个原因，

why the prediction didn't work,

为什么这个预测不准确。

because scientists were also assuming

因为科学家也假定

that the telescopes they had were sensitive enough

他们的天文望远镜足够灵敏，

to detect the parallax.

足以检测到这个视差。

And that turned out not to be true.

后来证明是错的。

It wasn't until the 19th century

直到19世纪

that scientists were able to detect

科学家才能检测出

the stellar parallax.

星球视差。

So, there's a third problem as well.

还有第三个问题。

The third problem is simply a factual problem,

这是现实问题，

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

许多的科学不适用教科书模型。

A lot of science isn't deductive at all,

许多的科学根本不是演绎，

it's actually inductive.

而是归纳出来的。

And by that we mean that scientists don't necessarily

这样的话，科学家并不需要

start with theories and hypotheses,

由理论和假设出发，

often they just start with observations

通常他们只是从观察出发，

of stuff going on in the world.

观察世界上的的一切。

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

最著名的例子是

famous scientists who ever lived, Charles Darwin.

最著名的科学家，查尔斯·达尔文。

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

当达尔文还年轻，在比格号上航行时，

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

他没有假设，他没有理论。

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

他只知道他希望成为科学家，

and he started to collect data.

他开始收集数据。

Mainly he knew that he hated medicine

主要是因为他讨厌医学，

because the sight of blood made him sick so

因为他晕血，

he had to have an alternative career path.

所以他必须选择另一条职业道路。

So he started collecting data.

所以他开始收集数据。

And he collected many things, including his famous finches.

他收集许多的东西， 包括他著名的雀鸟。

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

他收集这些雀鸟的时候， 会把它们扔到袋子里，

and he had no idea what they meant.

他并不知道它们意味着什么。

Many years later back in London,

许多年以后回到伦敦时，

Darwin looked at his data again and began

达尔文再次翻看他的数据，

to develop an explanation,

开始做出了一些解释，

and that explanation was the theory of natural selection.

这个解释就是自然选择论。

Besides inductive science,

除了归纳科学，

scientists also often participate in modeling.

科学家也常常进行建模。

One of the things scientists want to do in life

他们一生中最想做的事情

is to explain the causes of things.

就是解释事情的起因。

And how do we do that?

我们怎么做呢？

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

建立模型是一个方法，

that tests an idea.

可以用来测试一个想法。

So this is a picture of Henry Cadell,

这是亨利卡德尔的照片，

who was a Scottish geologist in the 19th century.

他是19世纪的苏格兰地理学家。

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

从服饰可以看出他是一个苏格兰人，

a deerstalker cap and Wellington boots.

猎鹿帽和威林顿靴。

(Laughter)

（笑声）

And Cadell wanted to answer the question,

卡德尔希望能回答这个问题，

how are mountains formed?

山是怎么形成的？

And one of the things he had observed

他观察到的一个事情是,

is that if you look at mountains like the Appalachians,

如果你注视山，比如阿帕拉契山脉时,

you often find that the rocks in them

你会发现山中的石头

are folded,

是叠层的，

and they're folded in a particular way,

它们由特定的方式堆叠而成，

which suggested to him

这显示

that they were actually being compressed from the side.

它们是由两侧挤压而成的。

And this idea would later play a major role

这个想法在之后的

in discussions of continental drift.

大陆漂移假说中扮演了重要角色。

So he built this model, this crazy contraption

所以他建造了这个模型， 这个疯狂的装置，

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

有杠杆、木头、独轮车、

buckets, a big sledgehammer.

木桶、大锤子，

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

我不知道他什么要穿威林顿靴。

Maybe it's going to rain.

也许要下雨了吧。

And he created this physical model in order

他建造了这个实物模型，

to demonstrate that you could, in fact, create

用来证明你事实上能在石头上，

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

或至少像这样在泥土上制造

that looked a lot like mountains

山石那样的纹路，

if you compressed them from the side.

只需要从侧面挤压它们。

So it was an argument about the cause of mountains.

这是关于山体形成的论证。

Nowadays, most scientists prefer to work inside,

如今，科学家们更希望 进行深入的研究，

so they don't build physical models so much

他们并不常常建立实物模型，

as to make computer simulations.

而是用计算机模拟。

But a computer simulation is a kind of a model.

但计算机模拟仅仅是一个模型。

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

一个数学模型，

and like the physical models of the 19th century,

正如19世纪的实物模型一样，

it's very important for thinking about causes.

思考起因是非常重要的。

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

所以应对气候变化最重要的问题就是，

we have tremendous amounts of evidence

我们有大量的证据表明

that the Earth is warming up.

地球正在升温。

This slide here, the black line shows

这页幻灯片中，黑色的线条显示

the measurements that scientists have taken

科学家们测量的

for the last 150 years

过去150年的统计结果，

showing that the Earth's temperature

显示了地球的温度

has steadily increased,

正在稳步升高，

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

尤其是最近的50年

there's been this dramatic increase

上升是显著的，

of nearly one degree centigrade,

几乎是1摄氏度，

or almost two degrees Fahrenheit.

或2华氏度。

So what, though, is driving that change?

那么是什么驱动了这个改变呢？

How can we know what's causing

我们怎么知道是什么导致了

the observed warming?

这么明显的升温呢？

Well, scientists can model it

科学家可以建模，

using a computer simulation.

用计算机进行模拟。

So this diagram illustrates a computer simulation

这张图展示了计算机模拟，

that has looked at all the different factors

考虑了各种

that we know can influence the Earth's climate,

可能影响地球气候的因素，

so sulfate particles from air pollution,

从空气污染中的硫酸盐颗粒，

volcanic dust from volcanic eruptions,

到火山喷发中的火山灰，

changes in solar radiation,

到太阳辐射的改变，

and, of course, greenhouse gases.

当然，还有温室气体。

And they asked the question,

他们问了这样一个问题，

what set of variables put into a model

在模型中加入什么样的变量

will reproduce what we actually see in real life?

能再现我们在真实生活中 看到的情况呢？

So here is the real life in black.

黑线表示真实观察的数据，

Here's the model in this light gray,

浅灰色表示模拟的数据，

and the answer is

答案是

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

在上述的模拟中加入SAT考试中的E，

all of the above.

也就是以上皆有。 （译注：SAT考试中最常见答案）

The only way you can reproduce

能再现所观察到的

the observed temperature measurements

温度测量数据的唯一的方法，

is with all of these things put together,

就是把所有的东西放到一起，

including greenhouse gases,

包括温室气体，

and in particular you can see that the increase

特别是我们可以观察到

in greenhouse gases tracks

在对温室气体数据

this very dramatic increase in temperature

追踪时显示温度的上升，

over the last 50 years.

在过去的50年非常明显。

And so this is why climate scientists say

所以这就是为什么气候学家称

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

我们不仅仅知道气候变化正在发生，

we know that greenhouse gases are a major part

我们还知道温室气体是主要的

of the reason why.

影响因素。

So now because there all these different things

由于科学家做的这些

that scientists do,

各种各样的事情，

the philosopher Paul Feyerabend famously said,

哲学家保罗·费耶阿本德 说过一句名言，

"The only principle in science

“在不影响进步的情况下，

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

科学界唯一个法则就是： 任何方法都可以。”

Now this quotation has often been taken out of context,

这句名言经常被断章取义，

because Feyerabend was not actually saying

因为费耶阿本德并不是说

that in science anything goes.

在科学上怎么都行。

What he was saying was,

他想说的

actually the full quotation is,

完整版的话应该是，

"If you press me to say

“如果你强制我说出

what is the method of science,

科学研究方法是什么，

I would have to say: anything goes."

我会说：任何方法都可以。"

What he was trying to say

他想要说的应该是

is that scientists do a lot of different things.

科学家做了许多不同的事情。

Scientists are creative.

科学家很有创造力。

But then this pushes the question back:

但这个问题又回来了，

If scientists don't use a single method,

如果科学家不用一种统一的方法，

then how do they decide

他们怎么决定

what's right and what's wrong?

什么是正确的或者错误的？

And who judges?

由谁来决定呢？

And the answer is, scientists judge,

答案是，由科学家决定，

and they judge by judging evidence.

他们依照证据决定。

Scientists collect evidence in many different ways,

科学家通过不同的方法收集证据，

but however they collect it,

但不论他们如何收集，

they have to subject it to scrutiny.

他们要审慎看待这些证据。

And this led the sociologist Robert Merton

这就导致了社会学家罗伯特 · 默顿

to focus on this question of how scientists

关注这样一个问题，即科学家该如何

scrutinize data and evidence,

审慎看待他们的证据和数据，

and he said they do it in a way he called

他将这种方法称之为

"organized skepticism."

“组织性怀疑”。

And by that he meant it's organized

“组织性”说明

because they do it collectively,

科学家合作收集数据，

they do it as a group,

他们作为团队一起工作，

and skepticism, because they do it from a position

“怀疑”说明他们对证据

of distrust.

持怀疑态度。

That is to say, the burden of proof

这就是说，关于证据的主要工作

is on the person with a novel claim.

落在了宣称自己 发现了新东西的人身上。

And in this sense, science is intrinsically conservative.

在这种情况下，科学的本质是保守。

It's quite hard to persuade the scientific community

想要说服科学界

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

称“我们发现了些东西，这是真的”很难。

So despite the popularity of the concept

尽管方式转变的观念

of paradigm shifts,

被广泛地接受，

what we find is that actually,

我们却发现

really major changes in scientific thinking

科学思维上的重要改变

are relatively rare in the history of science.

在科学史上十分罕见。

So finally that brings us to one more idea:

最后我们提出了另一个想法：

If scientists judge evidence collectively,

如果科学家集体评判证据，

this has led historians to focus on the question

这就导致历史学家聚焦在了

of consensus,

“共识”这一问题上，

and to say that at the end of the day,

在最后，

what science is,

什么是科学，

what scientific knowledge is,

科学知识是什么，

is the consensus of the scientific experts

这是科学专家达成的共识，

who through this process of organized scrutiny,

他们通过这种组织性的怀疑，

collective scrutiny,

合作的怀疑，

have judged the evidence

来评判证据

and come to a conclusion about it,

得出结论，

either yea or nay.

判断正误，

So we can think of scientific knowledge

所以我们可以认为科学知识

as a consensus of experts.

就是专家的共识。

We can also think of science as being

我们也能认为科学是

a kind of a jury,

一种陪审团下的产物，

except it's a very special kind of jury.

当然这个陪审团非常特别。

It's not a jury of your peers,

他们不是你的同辈组成的，

it's a jury of geeks.

他们是怪才组成的陪审团。

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

他们是由男博士女博士组成的，

and unlike a conventional jury,

不同于传统的陪审团

which has only two choices,

只有两种选择，

guilty or not guilty,

有罪或无罪，

the scientific jury actually has a number of choices.

科学陪审团有很多的选择。

Scientists can say yes, something's true.

科学家们能说，这是对的。

Scientists can say no, it's false.

他们能说，这是错的。

Or, they can say, well it might be true

他们也能说，这可能是对的，

but we need to work more and collect more evidence.

但我们需要更多的证据。

Or, they can say it might be true,

他们也能说，这可能是对的，

but we don't know how to answer the question

但我们不知道如何回答这个问题，

and we're going to put it aside

可以先放在一边，

and maybe we'll come back to it later.

之后再讨论。

That's what scientists call "intractable."

他们称这种情况“很棘手”。

But this leads us to one final problem:

但这把我们引向另一个问题：

If science is what scientists say it is,

如果科学是科学家定义的，

then isn't that just an appeal to authority?

那这是不是只诉诸权威呢？

And weren't we all taught in school

我们不是在学校学过，

that the appeal to authority is a logical fallacy?

诉诸权威是逻辑上的谬误吗？

Well, here's the paradox of modern science,

其实这是现代科学的悖论，

the paradox of the conclusion I think historians

我相信历史学家、

and philosophers and sociologists have come to,

哲学家和社会学家都会得出来的悖论，

that actually science is the appeal to authority,

事实上科学就是诉诸权威，

but it's not the authority of the individual,

但这不是对个人的权威，

no matter how smart that individual is,

不论这个人有多聪明，

like Plato or Socrates or Einstein.

像柏拉图，苏格拉底或爱因斯坦。

It's the authority of the collective community.

这是对精英群体的权威。

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

你可以把它理解成一种集体智慧，

but a very special kind of crowd.

但这个集体非常特别。

Science does appeal to authority,

科学确实诉诸权威，

but it's not based on any individual,

但不是诉诸个人，

no matter how smart that individual may be.

不论这个人多聪明。

It's based on the collective wisdom,

它建立于集体智慧之上，

the collective knowledge, the collective work,

建立于集体知识，集体工作之上，

of all of the scientists who have worked

建立于为这个问题努力过的

on a particular problem.

所有科学家之上。

Scientists have a kind of culture of collective distrust,

科学家有一种集体怀疑的文化，

this "show me" culture,

这就是“给我看”文化，

illustrated by this nice woman here

这个女士向我们展示了这一点，

showing her colleagues her evidence.

她在向她的同事展示她的证据。

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

当然，这些人并不像科学家，

because they're much too happy.

他们看起来太开心了。

(Laughter)

（笑声）

Okay, so that brings me to my final point.

最后，我想说：

Most of us get up in the morning.

我们大多数人要早起奔波。

Most of us trust our cars.

大多数人依赖我们的汽车。

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

瞧，我现在在曼哈顿，

this is a bad analogy,

这不是一个很好的类比，

but most Americans who don't live in Manhattan

但大多数美国人没住在曼哈顿，

get up in the morning and get in their cars

早上起来，钻进汽车，

and turn on that ignition, and their cars work,

点火，汽车就运转了，

and they work incredibly well.

运转得相当不错。

The modern automobile hardly ever breaks down.

现代的汽车基本不怎么抛锚。

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

为什么呢？ 为什么车能运行得这么好？

It's not because of the genius of Henry Ford

这不是因为亨利·福特的天才，

or Karl Benz or even Elon Musk.

也不是卡尔·奔驰或伊隆·马斯克。

It's because the modern automobile

这是因为现代的汽车

is the product of more than 100 years of work

是100多年努力的结晶，

by hundreds and thousands

是成百上千，

and tens of thousands of people.

甚至上万人的努力。

The modern automobile is the product

现代汽车是

of the collected work and wisdom and experience

集体工作和智慧及经验的产物，

of every man and woman who has ever worked

是所有为汽车工作过的

on a car,

男人和女人的产物，

and the reliability of the technology is the result

这项技术的可靠性就是

of that accumulated effort.

这些付出加起来的结果。

We benefit not just from the genius of Benz

我们不仅仅从奔驰，福特和马斯克的

and Ford and Musk

天才中获益，

but from the collective intelligence and hard work

而是从所有为现代汽车

of all of the people who have worked

奋斗的人们的

on the modern car.

集体智慧和工作中获益。

And the same is true of science,

科学界也一样，

only science is even older.

只是科学更加古老。

Our basis for trust in science is actually the same

我们信任科学的基石，

as our basis in trust in technology,

与我们信任技术的基石是一样的，

and the same as our basis for trust in anything,

与我们信任其他事物的基石 都是一样的，

namely, experience.

也就是，经验。

But it shouldn't be blind trust

但这不应该是盲目的信任，

any more than we would have blind trust in anything.

不能盲目信任任何事情。

Our trust in science, like science itself,

我们对科学的信任如同科学本身，

should be based on evidence,

应该建立于证据，

and that means that scientists

这意味着科学家

have to become better communicators.

应该善于沟通。

They have to explain to us not just what they know

他们不仅必须向我们 解释他们知道的东西，

but how they know it,

还要解释他们知道的过程，

and it means that we have to become better listeners.

这意味着我们需要变为更好的聆听者。

Thank you very much.

十分感谢。

(Applause)

（鼓掌）