TEDxLondonBusinessSchool
Alex Edmans: What to trust in a "post-truth" world
亚历克斯·爱德蒙斯: 在后真相的世界里该相信什么
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研究员亚历克斯·爱德蒙斯说，只有当你真正愿意接受犯错的可能性时，你才会成长。在一次见解深刻的演讲中，他探讨了证实偏差(即倾向于只接受支持个人信仰的信息)是如何让你在社交媒体、政治和其他领域误入歧途的，并提供了三个实用的建议来帮助你寻找真正的信仰。(比如:指定某人做你生活中的魔鬼代言人。)
Alex Edmans - Finance professor, editor
Alex Edmans uses rigorous academic research to influence real-life business practices -- in particular, how companies can pursue purpose as well as profit. Full bio
Alex Edmans uses rigorous academic research to influence real-life business practices -- in particular, how companies can pursue purpose as well as profit. Full bio
Double-click the English transcript below to play the video.
00:13
Belle Gibson was a happy young Australian.
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贝尔·吉布森是一个
快乐的澳大利亚年轻人。
快乐的澳大利亚年轻人。
她住在珀斯，
她喜欢玩滑板。
她喜欢玩滑板。
00:16
She lived in Perth,
and she loved skateboarding.
and she loved skateboarding.
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00:20
But in 2009, Belle learned that she had
brain cancer and four months to live.
brain cancer and four months to live.
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但在2009年，
贝尔得知自己患有脑癌，
贝尔得知自己患有脑癌，
并且只有四个月可活。
00:25
Two months of chemo
and radiotherapy had no effect.
and radiotherapy had no effect.
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两个月的化疗和放疗没有见效。
00:29
But Belle was determined.
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但是贝尔的意志很坚强，
贝尔一直都是一位斗士。
00:30
She'd been a fighter her whole life.
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从6岁起，
她就得给患自闭症的哥哥，
她就得给患自闭症的哥哥，
00:32
From age six, she had to cook
for her brother, who had autism,
for her brother, who had autism,
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还有患多发性硬化症的母亲做饭。
00:36
and her mother,
who had multiple sclerosis.
who had multiple sclerosis.
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她的父亲一直缺位。
00:38
Her father was out of the picture.
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00:40
So Belle fought, with exercise,
with meditation
with meditation
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因此，贝尔用锻炼、冥想抗癌
同时，她也用蔬果代替肉食。
00:44
and by ditching meat
for fruit and vegetables.
for fruit and vegetables.
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00:47
And she made a complete recovery.
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她完全康复了。
00:50
Belle's story went viral.
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贝尔的故事迅速走红。
她的故事在推特和博客上广为流传。
00:52
It was tweeted, blogged about,
shared and reached millions of people.
shared and reached millions of people.
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00:56
It showed the benefits of shunning
traditional medicine
traditional medicine
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它展示了传统医学以外的
饮食和锻炼的意义。
00:59
for diet and exercise.
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01:01
In August 2013, Belle launched
a healthy eating app,
a healthy eating app,
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2013年8月，贝尔发布了
一款健康饮食的应用软件，
一款健康饮食的应用软件，
“健康厨房”
01:05
The Whole Pantry,
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首月下载量达到20万次。
01:07
downloaded 200,000 times
in the first month.
in the first month.
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01:13
But Belle's story was a lie.
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但贝尔的故事是个谎言。
01:17
Belle never had cancer.
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贝尔从来没有过癌症。
01:19
People shared her story
without ever checking if it was true.
without ever checking if it was true.
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人们分享她的故事时
从未去检验其真实性。
从未去检验其真实性。
01:24
This is a classic example
of confirmation bias.
of confirmation bias.
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这是肯证偏差的典型例子。
01:28
We accept a story uncritically
if it confirms what we'd like to be true.
if it confirms what we'd like to be true.
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我们会不加批判地接受一个故事，
当它证实了我们认为是真实的事时，
01:33
And we reject any story
that contradicts it.
that contradicts it.
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并且我们会拒绝
任何与之相悖的故事。
任何与之相悖的故事。
01:36
How often do we see this
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我们看到了多少这种情况？
在我们分享却忽略的故事中。
01:38
in the stories
that we share and we ignore?
that we share and we ignore?
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在政治上，在商业中，
在健康建议上。
在健康建议上。
01:41
In politics, in business,
in health advice.
in health advice.
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01:47
The Oxford Dictionary's
word of 2016 was "post-truth."
word of 2016 was "post-truth."
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牛津词典2016年的
年度词汇是“后真相”。
年度词汇是“后真相”。
01:51
And the recognition that we now live
in a post-truth world
in a post-truth world
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人们意识到
我们正处在后真相世界中，
我们正处在后真相世界中，
所以如今我们非常强调核查事实。
01:55
has led to a much needed emphasis
on checking the facts.
on checking the facts.
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01:59
But the punch line of my talk
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但我演讲的重点是
仅仅去核查真相还不够。
02:00
is that just checking
the facts is not enough.
the facts is not enough.
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02:04
Even if Belle's story were true,
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即便贝尔的故事是真的，
它也是一个不相关的故事。
02:07
it would be just as irrelevant.
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02:10
Why?
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为什么？
02:11
Well, let's look at one of the most
fundamental techniques in statistics.
fundamental techniques in statistics.
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让我们看看统计学中的
一个基本原理。
一个基本原理。
贝叶斯推理。
02:15
It's called Bayesian inference.
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02:18
And the very simple version is this:
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它的核心观点就是，
我们关心：“数据是否支持这个理论？”
02:21
We care about "does the data
support the theory?"
support the theory?"
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02:25
Does the data increase our belief
that the theory is true?
that the theory is true?
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这个数据是否能够证实
这个理论为真
这个理论为真
02:29
But instead, we end up asking,
"Is the data consistent with the theory?"
"Is the data consistent with the theory?"
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但相反，我们最终会问，
“数据是否与理论一致？”
“数据是否与理论一致？”
02:34
But being consistent with the theory
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但与理论一致
不等于数据支持这个理论。
02:37
does not mean that the data
supports the theory.
supports the theory.
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02:40
Why?
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为什么？
因为有一个关键但被人遗忘的点——
02:41
Because of a crucial
but forgotten third term --
but forgotten third term --
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数据也可以和对立的理论一致。
02:45
the data could also be consistent
with rival theories.
with rival theories.
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02:49
But due to confirmation bias,
we never consider the rival theories,
we never consider the rival theories,
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但由于肯证偏差，
我们从不考虑对立的理论，
我们从不考虑对立的理论，
因为我们袒护
我们的宠物理论。
我们的宠物理论。
02:54
because we're so protective
of our own pet theory.
of our own pet theory.
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02:58
Now, let's look at this for Belle's story.
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现在，让我们看看贝尔的故事。
我们关心的是：贝尔的故事
03:01
Well, we care about:
Does Belle's story support the theory
Does Belle's story support the theory
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支持饮食治愈癌症的理论吗？
03:05
that diet cures cancer?
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但相反，我们最终问的是：
03:06
But instead, we end up asking,
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“贝尔的故事
等同于饮食治愈癌症吗？”
等同于饮食治愈癌症吗？”
03:08
"Is Belle's story consistent
with diet curing cancer?"
with diet curing cancer?"
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03:13
And the answer is yes.
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答案是肯定的。
03:15
If diet did cure cancer,
we'd see stories like Belle's.
we'd see stories like Belle's.
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如果饮食可以治愈癌症，
我们会看到像贝尔这样的故事。
03:20
But even if diet did not cure cancer,
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但即便饮食不能治疗癌症，
我们仍然会看到像贝尔这样的故事。
03:23
we'd still see stories like Belle's.
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03:26
A single story in which
a patient apparently self-cured
a patient apparently self-cured
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比如一个病人自我治愈
只是因为一开始被误诊。
03:31
just due to being misdiagnosed
in the first place.
in the first place.
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03:35
Just like, even if smoking
was bad for your health,
was bad for your health,
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或者，即使吸烟有害健康，
你仍然会看到一个烟民活到100岁。
03:39
you'd still see one smoker
who lived until 100.
who lived until 100.
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03:42
(Laughter)
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（笑声）
03:44
Just like, even if education
was good for your income,
was good for your income,
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又或者，即使接受教育
有助于增加你的收入，
有助于增加你的收入，
你仍会看到没上过大学的千万富翁。
03:46
you'd still see one multimillionaire
who didn't go to university.
who didn't go to university.
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（笑声）
03:51
(Laughter)
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所以贝尔故事最大的问题
不在于它是虚假的。
不在于它是虚假的。
03:56
So the biggest problem with Belle's story
is not that it was false.
is not that it was false.
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在于它只是一个故事。
03:59
It's that it's only one story.
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04:03
There might be thousands of other stories
where diet alone failed,
where diet alone failed,
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也许有成千上万仅靠饮食失败的故事，
但我们从没听到这些故事。
04:07
but we never hear about them.
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04:10
We share the outlier cases
because they are new,
because they are new,
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我们分享异常个案
只是因为它们是新奇的，
只是因为它们是新奇的，
因此它们成了新闻。
04:14
and therefore they are news.
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04:16
We never share the ordinary cases.
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我们从不分享普通案例。
它们太普通，
它们就是日常发生的事情。
它们就是日常发生的事情。
04:19
They're too ordinary,
they're what normally happens.
they're what normally happens.
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04:23
And that's the true
99 percent that we ignore.
99 percent that we ignore.
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这是我们忽略的99%的真相。
就像在社会中，
04:26
Just like in society, you can't just
listen to the one percent,
listen to the one percent,
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你不能只听1%的异常个案，
04:29
the outliers,
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去忽略99%的普通事实。
04:30
and ignore the 99 percent, the ordinary.
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04:34
Because that's the second example
of confirmation bias.
of confirmation bias.
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因为这是第二个肯证偏差的例子，
我们接受事实作为数据。
04:37
We accept a fact as data.
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04:41
The biggest problem is not
that we live in a post-truth world;
that we live in a post-truth world;
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最大的问题不在于
我们生活在后真相世界；
我们生活在后真相世界；
在于我们生活在后数据世界。
04:45
it's that we live in a post-data world.
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04:49
We prefer a single story to tons of data.
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比起大量的数据，
我们更喜欢简单的故事。
我们更喜欢简单的故事。
04:54
Now, stories are powerful,
they're vivid, they bring it to life.
they're vivid, they bring it to life.
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那些强大的，生动的，鲜活的故事。
他们告诉你
演讲要用故事开场。
演讲要用故事开场。
04:57
They tell you to start
every talk with a story.
every talk with a story.
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我也是这样做的。
05:00
I did.
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05:01
But a single story
is meaningless and misleading
is meaningless and misleading
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但一个简单的故事
是没有意义且误导人的，
是没有意义且误导人的，
除非它有大量的数据支持。
05:06
unless it's backed up by large-scale data.
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05:11
But even if we had large-scale data,
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但即便我们有大量的数据，
这可能仍然不够。
05:13
that might still not be enough.
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05:16
Because it could still be consistent
with rival theories.
with rival theories.
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因为它可能仍然与对立结论一致。
05:20
Let me explain.
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让我解释一下。
05:22
A classic study
by psychologist Peter Wason
by psychologist Peter Wason
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心理学家彼得·沃森的一项经典研究
给你一组三个数据
05:25
gives you a set of three numbers
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并让你思考产生这些数据的规律。
05:27
and asks you to think of the rule
that generated them.
that generated them.
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05:30
So if you're given two, four, six,
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如果他们给了你三个数字：
2，4，6，
2，4，6，
规律是什么？
05:35
what's the rule?
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05:36
Well, most people would think,
it's successive even numbers.
it's successive even numbers.
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很多人会认为，这是连续的偶数。
05:40
How would you test it?
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你会如何检验它？
你可以提出其他连续偶数的组合：
05:42
Well, you'd propose other sets
of successive even numbers:
of successive even numbers:
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4，6，8或者12，14，16.
05:45
4, 6, 8 or 12, 14, 16.
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05:49
And Peter would say these sets also work.
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彼得说这些数组也行。
05:53
But knowing that these sets also work,
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但知道这些数组也行，
知道数百组连续的偶数也可以，
05:55
knowing that perhaps hundreds of sets
of successive even numbers also work,
of successive even numbers also work,
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这个结论形同虚设。
06:00
tells you nothing.
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06:02
Because this is still consistent
with rival theories.
with rival theories.
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因为这仍然与对立理论一致。
06:06
Perhaps the rule
is any three even numbers.
is any three even numbers.
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也许规则可能是任意三个偶数。
06:11
Or any three increasing numbers.
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或者任何三个不断增加的数字。
06:14
And that's the third example
of confirmation bias:
of confirmation bias:
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这是第三个肯证偏差的例子：
接受数据作为证据，
06:17
accepting data as evidence,
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即便它与对立结论一致。
06:20
even if it's consistent
with rival theories.
with rival theories.
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06:24
Data is just a collection of facts.
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数据只是事实的组合。
06:28
Evidence is data that supports
one theory and rules out others.
one theory and rules out others.
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证据是支持一种理论
排除其他理论的数据。
排除其他理论的数据。
06:34
So the best way to support your theory
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所以支持你的理论最好的方法是
试图去反驳它，
做魔鬼的代言人（唱反调）。
做魔鬼的代言人（唱反调）。
06:37
is actually to try to disprove it,
to play devil's advocate.
to play devil's advocate.
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06:41
So test something, like 4, 12, 26.
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所以检验一下，
比如4，12，26.
比如4，12，26.
06:46
If you got a yes to that,
that would disprove your theory
that would disprove your theory
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如果你的答案是肯定的，
那么就证明
你的连续偶数理论是不成立的。
你的连续偶数理论是不成立的。
06:50
of successive even numbers.
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06:53
Yet this test is powerful,
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这个检验很有力，
因为如果答案不是，
就可以排除“任何三个偶数”
就可以排除“任何三个偶数”
06:55
because if you got a no, it would rule out
"any three even numbers"
"any three even numbers"
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和“任何三个不断增长的数字”。
07:00
and "any three increasing numbers."
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它会排除对立理论，
但不排除你的理论。
但不排除你的理论。
07:01
It would rule out the rival theories,
but not rule out yours.
but not rule out yours.
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07:05
But most people are too afraid
of testing the 4, 12, 26,
of testing the 4, 12, 26,
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但大部分人
不敢用4，12，26检验，
不敢用4，12，26检验，
因为他们不想肯定，
07:10
because they don't want to get a yes
and prove their pet theory to be wrong.
and prove their pet theory to be wrong.
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也不想承认他们的宠物理论是错的。
07:16
Confirmation bias is not only
about failing to search for new data,
about failing to search for new data,
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肯证偏差不仅指
未能搜索到新的数据，
未能搜索到新的数据，
它也与你误解数据有关。
07:22
but it's also about misinterpreting
data once you receive it.
data once you receive it.
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07:26
And this applies outside the lab
to important, real-world problems.
to important, real-world problems.
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这个理论也适用于
实验室外的现实世界。
实验室外的现实世界。
的确，托马斯•爱迪生有句名言
07:29
Indeed, Thomas Edison famously said,
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我没有失败，
07:33
"I have not failed,
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我成功地发现了1万种行不通的方法
07:35
I have found 10,000 ways that won't work."
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07:40
Finding out that you're wrong
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发现你的错误
是通往成功的唯一道路。
07:42
is the only way to find out what's right.
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07:46
Say you're a university
admissions director
admissions director
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假设你是大学招生办主任，
你的理论是只有来自富裕家庭
07:49
and your theory is that only
students with good grades
students with good grades
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成绩好的学生才表现好。
07:52
from rich families do well.
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07:54
So you only let in such students.
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所以你只招这些学生，
他们都表现很好。
07:56
And they do well.
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07:58
But that's also consistent
with the rival theory.
with the rival theory.
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但这也跟对立理论一致。
08:01
Perhaps all students
with good grades do well,
with good grades do well,
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可能所有成绩好的学生都表现好，
不论富裕或贫穷。
08:04
rich or poor.
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08:06
But you never test that theory
because you never let in poor students
because you never let in poor students
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但你永远不会测试这个理论，
因为你不会招贫穷学生，
因为你不想被证明错误。
08:10
because you don't want to be proven wrong.
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08:14
So, what have we learned?
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那么，我们学到了什么？
08:17
A story is not fact,
because it may not be true.
because it may not be true.
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一个故事不是事实，
因为它可能不是真的。
因为它可能不是真的。
08:21
A fact is not data,
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一个事实不是数据，
如果只是一个数据点，
它可能不具有代表性。
它可能不具有代表性。
08:23
it may not be representative
if it's only one data point.
if it's only one data point.
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08:28
And data is not evidence --
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数据不是证据——
如果它与对立理论一致，
就不具有支持性。
就不具有支持性。
08:31
it may not be supportive
if it's consistent with rival theories.
if it's consistent with rival theories.
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08:36
So, what do you do?
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你会怎么做？
08:39
When you're at
the inflection points of life,
the inflection points of life,
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当你处在人生的转折点，
去选择生意的策略，
08:42
deciding on a strategy for your business,
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孩子的育儿技巧，
08:44
a parenting technique for your child
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或者健康养生，
08:47
or a regimen for your health,
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你如何确保你不是基于故事
08:49
how do you ensure
that you don't have a story
that you don't have a story
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而是你拥有证据？
08:53
but you have evidence?
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08:56
Let me give you three tips.
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让我给你们三个提示。
08:58
The first is to actively seek
other viewpoints.
other viewpoints.
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首先是积极寻求其他观点。
阅读和倾听你公然不同意的人。
09:02
Read and listen to people
you flagrantly disagree with.
you flagrantly disagree with.
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在你看来，他们说的90%都不对。
09:06
Ninety percent of what they say
may be wrong, in your view.
may be wrong, in your view.
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09:10
But what if 10 percent is right?
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但如果还有10%是对的呢？
09:13
As Aristotle said,
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亚里士多德说过，
“受过教育的标志是，
09:15
"The mark of an educated man
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你可以不接受一种观点，
09:17
is the ability to entertain a thought
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但你能容纳它。”
09:21
without necessarily accepting it."
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09:24
Surround yourself with people
who challenge you,
who challenge you,
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和挑战你的人在一起，
创造一种积极鼓励异见的环境。
09:26
and create a culture
that actively encourages dissent.
that actively encourages dissent.
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09:31
Some banks suffered from groupthink,
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一些银行受到群体思维的影响，
员工不敢挑战管理者的借贷决策，
09:33
where staff were too afraid to challenge
management's lending decisions,
management's lending decisions,
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引发了金融危机。
09:38
contributing to the financial crisis.
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09:41
In a meeting, appoint someone
to be devil's advocate
to be devil's advocate
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开会的时候，
指定某人充当魔鬼的代言人
指定某人充当魔鬼的代言人
挑战你的宠物理论。
09:45
against your pet idea.
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09:47
And don't just hear another viewpoint --
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不要只让这些观点从你的脑后飘过，
请认真倾听。
09:50
listen to it, as well.
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09:53
As psychologist Stephen Covey said,
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正如心理学家斯蒂芬·柯维所说，
“抱着理解的态度倾听，
09:55
"Listen with the intent to understand,
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别只想着怎么回答。”
09:59
not the intent to reply."
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10:01
A dissenting viewpoint
is something to learn from
is something to learn from
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对立的观点是值得学习的，
而不是不假思索地反对。
10:05
not to argue against.
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10:07
Which takes us to the other
forgotten terms in Bayesian inference.
forgotten terms in Bayesian inference.
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这使我们想到
贝叶斯推断中被遗忘的部分
贝叶斯推断中被遗忘的部分
10:12
Because data allows you to learn,
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因为数据给你学习的空间，
但学习只是一个起点。
10:14
but learning is only relative
to a starting point.
to a starting point.
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如果开始就完全确信
你的宠物理论必然成立，
你的宠物理论必然成立，
10:18
If you started with complete certainty
that your pet theory must be true,
that your pet theory must be true,
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那么你的观点不会改变——
10:23
then your view won't change --
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不管你看到的数据是什么。
10:25
regardless of what data you see.
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10:28
Only if you are truly open
to the possibility of being wrong
to the possibility of being wrong
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只有你真正接受犯错的可能性时，
你才能学习。
10:33
can you ever learn.
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10:35
As Leo Tolstoy wrote,
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正如列夫·托尔斯泰所写，
“最难的事情
10:37
"The most difficult subjects
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也可以向最迟钝的人解释清楚，
10:39
can be explained to the most
slow-witted man
slow-witted man
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只要他还没有
形成任何关于此问题的见解。
形成任何关于此问题的见解。
10:43
if he has not formed
any idea of them already.
any idea of them already.
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10:46
But the simplest thing
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但最简单的事情
却无法向最聪明的人说清楚，
10:48
cannot be made clear
to the most intelligent man
to the most intelligent man
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如果他确信他已经知道答案。“
10:51
if he is firmly persuaded
that he knows already."
that he knows already."
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10:56
Tip number two is "listen to experts."
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第二个提示是：“听专家的。”
11:01
Now, that's perhaps the most
unpopular advice that I could give you.
unpopular advice that I could give you.
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这可能是我给你的
最不流行的建议了。
最不流行的建议了。
（笑声）
11:04
(Laughter)
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英国政治家迈克尔·戈夫曾说过:
11:05
British politician Michael Gove
famously said that people in this country
famously said that people in this country
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这个国家的人民已经受够专家了。
11:10
have had enough of experts.
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11:13
A recent poll showed that more people
would trust their hairdresser --
would trust their hairdresser --
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最近的调查显示
更多人相信他们的理发师——
更多人相信他们的理发师——
（笑声）
11:17
(Laughter)
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或者街上的路人，
11:19
or the man on the street
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而非商界领袖、医疗服务机构、
甚至慈善机构的领导人。
甚至慈善机构的领导人。
11:21
than they would leaders of businesses,
the health service and even charities.
the health service and even charities.
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11:26
So we respect a teeth-whitening formula
discovered by a mom,
discovered by a mom,
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所以我们敬仰一位母亲
发现的牙齿美白配方，
发现的牙齿美白配方，
或者我们会听
女演员对疫苗接种的看法。
女演员对疫苗接种的看法。
11:30
or we listen to an actress's view
on vaccination.
on vaccination.
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我们喜欢说实话、凭直觉做事的人，
11:33
We like people who tell it like it is,
who go with their gut,
who go with their gut,
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我们觉得这叫真实。
11:36
and we call them authentic.
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11:38
But gut feel can only get you so far.
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3214
但直觉只能让你走这么远。
11:42
Gut feel would tell you never to give
water to a baby with diarrhea,
water to a baby with diarrhea,
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4436
直觉会告诉你永远不要
给腹泻的婴儿喝水，
给腹泻的婴儿喝水，
因为它会从另外一端流出。
11:47
because it would just
flow out the other end.
flow out the other end.
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专家告诉你，事实并非如此。
11:49
Expertise tells you otherwise.
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11:53
You'd never trust your surgery
to the man on the street.
to the man on the street.
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你绝不会把你的手术交给街上的人。
11:56
You'd want an expert
who spent years doing surgery
who spent years doing surgery
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你想要一个拥有多年手术经验
并且有最佳技巧的专家。
12:00
and knows the best techniques.
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12:03
But that should apply
to every major decision.
to every major decision.
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3133
但这点应该应用到每个重要的决定中。
12:07
Politics, business, health advice
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4556
政治，商业，健康建议都需要专家，
12:11
require expertise, just like surgery.
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2896
就跟做手术一样。
12:16
So then, why are experts so mistrusted?
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3539
那么，为什么专家如此不被信任呢？
12:20
Well, one reason
is they're seen as out of touch.
is they're seen as out of touch.
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3239
一个原因是他们脱离群众。
一个年薪百万的总裁
不可能为街头的人发声。
不可能为街头的人发声。
12:24
A millionaire CEO couldn't possibly
speak for the man on the street.
speak for the man on the street.
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4090
12:29
But true expertise is found on evidence.
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3559
但真正的专业知识来自于证据。
12:33
And evidence stands up
for the man on the street
for the man on the street
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证据支持街上的人，
反对精英。
12:36
and against the elites.
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12:38
Because evidence forces you to prove it.
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因为证据迫使你证明它。
12:41
Evidence prevents the elites
from imposing their own view
from imposing their own view
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证据不允许精英们强加他们的观点
在没有证明的情况下。
12:46
without proof.
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12:49
A second reason
why experts are not trusted
why experts are not trusted
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2071
第二个专家不被信任的理由是，
不同的专家观点不同。
12:51
is that different experts
say different things.
say different things.
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只要有专家说
脱欧对英国而言弊端重重，
脱欧对英国而言弊端重重，
12:54
For every expert who claimed that leaving
the EU would be bad for Britain,
the EU would be bad for Britain,
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就会有另外一个专家说
脱欧对英国而言好处良多。
脱欧对英国而言好处良多。
12:58
another expert claimed it would be good.
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这些所谓的专家，
他们一半的观点都是错的。
他们一半的观点都是错的。
13:01
Half of these so-called experts
will be wrong.
will be wrong.
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13:05
And I have to admit that most papers
written by experts are wrong.
written by experts are wrong.
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我不得不承认，大多数专家
写的论文也都是错的。
写的论文也都是错的。
13:10
Or at best, make claims that
the evidence doesn't actually support.
the evidence doesn't actually support.
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换一种好听一点的说法，
做出证据并不支持的断言。
13:14
So we can't just take
an expert's word for it.
an expert's word for it.
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所以我们不能只相信专家。
13:18
In November 2016, a study
on executive pay hit national headlines.
on executive pay hit national headlines.
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2016年11月，一个关于
高管薪酬的研究登上国家头条。
高管薪酬的研究登上国家头条。
13:25
Even though none of the newspapers
who covered the study
who covered the study
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尽管报道这项研究的报社
没有一家看过这项研究。
13:28
had even seen the study.
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13:30
It wasn't even out yet.
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这项研究甚至还没有发表。
13:32
They just took the author's word for it,
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2204
他们只是把作者的话当真了，
13:35
just like with Belle.
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就像贝尔的故事一样。
13:38
Nor does it mean that we can
just handpick any study
just handpick any study
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这不意味着我们可以随便挑选一个
刚好支持我们观点的研究——
13:40
that happens to support our viewpoint --
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2111
这也是肯证偏差。
13:42
that would, again, be confirmation bias.
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也不意味着7项研究表明A，
13:44
Nor does it mean
that if seven studies show A
that if seven studies show A
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2555
三项研究表明B，
13:47
and three show B,
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A就必然是真的。
13:49
that A must be true.
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1483
13:51
What matters is the quality,
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重点在于质量，
而不是专家的数量。
13:53
and not the quantity of expertise.
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13:57
So we should do two things.
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所以我们应该做两件事。
14:00
First, we should critically examine
the credentials of the authors.
the credentials of the authors.
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4578
首先，我们应该
严格审查作者的资历，
严格审查作者的资历，
14:05
Just like you'd critically examine
the credentials of a potential surgeon.
the credentials of a potential surgeon.
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就像你会谨慎地审视一个
外科医生的资质一样。
14:10
Are they truly experts in the matter,
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他们真的是这个领域的专家吗，
或者他们有没有既得利益？
14:13
or do they have a vested interest?
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2267
14:16
Second, we should pay particular attention
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第二，我们应该特别注意
发布在顶级期刊上的论文。
14:19
to papers published
in the top academic journals.
in the top academic journals.
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14:24
Now, academics are often accused
of being detached from the real world.
of being detached from the real world.
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如今，
学术界常常被指责与现实世界脱节。
学术界常常被指责与现实世界脱节。
14:28
But this detachment gives you
years to spend on a study.
years to spend on a study.
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但这种脱节
给了你充足的时间去研究。
给了你充足的时间去研究。
去真正确定一个结果，
14:32
To really nail down a result,
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去排除那些对立的理论，
14:34
to rule out those rival theories,
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并且区分因果关系。
14:36
and to distinguish correlation
from causation.
from causation.
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3134
14:40
And academic journals involve peer review,
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868172
3477
学术期刊涉及同行评议，
在这个环节，论文会被严格审查
14:43
where a paper is rigorously scrutinized
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2294
（笑声）
14:45
(Laughter)
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1419
被学术界的尖端代表审查。
14:47
by the world's leading minds.
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875434
1934
14:50
The better the journal,
the higher the standard.
the higher the standard.
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2556
越好的期刊，标准越高。
最顶级期刊的论文拒绝率高达95%
14:53
The most elite journals
reject 95 percent of papers.
reject 95 percent of papers.
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5148
14:59
Now, academic evidence is not everything.
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3333
如今，学术证据并不是一切。
15:03
Real-world experience is critical, also.
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2667
现实世界的经验也很重要。
15:06
And peer review is not perfect,
mistakes are made.
mistakes are made.
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3400
同行评议也不尽完美，常犯错误。
15:10
But it's better to go
with something checked
with something checked
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2063
但有检查
总比没有检查好。
15:12
than something unchecked.
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1667
15:14
If we latch onto a study
because we like the findings,
because we like the findings,
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3199
如果我们青睐一个研究
是因为我们喜欢这个发现，
是因为我们喜欢这个发现，
而不考虑它是谁做的
或者它是否经过审查，
或者它是否经过审查，
15:17
without considering who it's by
or whether it's even been vetted,
or whether it's even been vetted,
271
905919
3888
这个研究就很有可能误导人。
15:21
there is a massive chance
that that study is misleading.
that that study is misleading.
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3627
15:26
And those of us who claim to be experts
273
914894
2580
我们这些自称专家的人，
需要认识到我们分析能力的局限性。
15:29
should recognize the limitations
of our analysis.
of our analysis.
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3253
15:33
Very rarely is it possible to prove
or predict something with certainty,
or predict something with certainty,
275
921244
4563
确切地证明或预测某事
的可能性是很小的，
的可能性是很小的，
15:38
yet it's so tempting to make
a sweeping, unqualified statement.
a sweeping, unqualified statement.
276
926292
4369
然而，发表一份全面、
不够格的声明十分诱人。
不够格的声明十分诱人。
15:43
It's easier to turn into a headline
or to be tweeted in 140 characters.
or to be tweeted in 140 characters.
277
931069
4344
它们往往能成为头条
或者微博热点
或者微博热点
15:48
But even evidence may not be proof.
278
936417
3142
即便证据并不充分详实。
15:52
It may not be universal,
it may not apply in every setting.
it may not apply in every setting.
279
940481
4210
它可能不是通用的，
可能不适用于任何条件。
可能不适用于任何条件。
15:57
So don't say, "Red wine
causes longer life,"
causes longer life,"
280
945252
4920
所以不要说，
“红酒能延长寿命，”
“红酒能延长寿命，”
当证据只是在
红酒与长寿相关时，
红酒与长寿相关时，
16:02
when the evidence is only that red wine
is correlated with longer life.
is correlated with longer life.
281
950196
4682
16:07
And only then in people
who exercise as well.
who exercise as well.
282
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2770
并且样本局限在运动人群中。
16:11
Tip number three
is "pause before sharing anything."
is "pause before sharing anything."
283
959868
3966
提示三：
“分享任何事情前先三思。”
“分享任何事情前先三思。”
16:16
The Hippocratic oath says,
"First, do no harm."
"First, do no harm."
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964907
3464
希波克拉底誓言（医者誓言）说，
“首先，不要伤害。”
“首先，不要伤害。”
16:21
What we share is potentially contagious,
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我们分享的东西
有可能会快速蔓延，
有可能会快速蔓延，
所以要谨慎地对待
我们散布的东西。
我们散布的东西。
16:24
so be very careful about what we spread.
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16:28
Our goal should not be
to get likes or retweets.
to get likes or retweets.
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我们的目的不应该是为了
获得点赞或转发。
获得点赞或转发。
否则，我们只会分享共识；
16:31
Otherwise, we only share the consensus;
we don't challenge anyone's thinking.
we don't challenge anyone's thinking.
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我们不会挑战任何人的思考。
16:36
Otherwise, we only share what sounds good,
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否则，我们只分享听起来好的，
无视其是否是证据。
16:39
regardless of whether it's evidence.
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16:42
Instead, we should ask the following:
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反过来，我们应该问如下问题：
16:45
If it's a story, is it true?
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如果这是个故事，这是真的吗？
如果这是真的，
有大量的证据支持吗？
有大量的证据支持吗？
16:47
If it's true, is it backed up
by large-scale evidence?
by large-scale evidence?
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如果有，证据是谁提供的，
他们的凭证是什么？
他们的凭证是什么？
16:50
If it is, who is it by,
what are their credentials?
what are their credentials?
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它发表了吗？
这个期刊是否足够权威？
这个期刊是否足够权威？
16:53
Is it published,
how rigorous is the journal?
how rigorous is the journal?
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16:56
And ask yourself
the million-dollar question:
the million-dollar question:
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并且郑重地问自己，
16:59
If the same study was written by the same
authors with the same credentials
authors with the same credentials
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如果同样的研究
是同等资质的同一作者写的，
是同等资质的同一作者写的，
17:05
but found the opposite results,
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但发现的是对立理论，
17:07
would you still be willing
to believe it and to share it?
to believe it and to share it?
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你仍然愿意相信和分享它吗？
17:13
Treating any problem --
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处理任何问题——
国家经济问题或者个人健康问题，
17:15
a nation's economic problem
or an individual's health problem,
or an individual's health problem,
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很难。
17:19
is difficult.
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17:21
So we must ensure that we have
the very best evidence to guide us.
the very best evidence to guide us.
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所以我们必须确保
有最佳证据指引我们。
有最佳证据指引我们。
17:26
Only if it's true can it be fact.
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只有它是真的，才能成为事实。
17:29
Only if it's representative
can it be data.
can it be data.
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只有具有代表性，才能成为数据。
17:33
Only if it's supportive
can it be evidence.
can it be evidence.
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只有被支持，才能是证据。
只有是证据，我们才能从后真相世界
17:36
And only with evidence
can we move from a post-truth world
can we move from a post-truth world
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走向支持真相的世界。
17:41
to a pro-truth world.
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17:44
Thank you very much.
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谢谢。
（鼓掌）
17:45
(Applause)
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ABOUT THE SPEAKER
Alex Edmans - Finance professor, editorAlex Edmans uses rigorous academic research to influence real-life business practices -- in particular, how companies can pursue purpose as well as profit.
Why you should listen
Alex Edmans is professor of finance at London Business School and managing editor of the Review of Finance, the leading academic finance journal in Europe. He is an expert in corporate governance, executive compensation, corporate social responsibility and behavioral economics.
Edmans has a unique combination of deep academic rigor and practical business experience. He's particularly passionate about translating complex academic research into practical ideas that can then be applied to real-life problems. He has spoken at the World Economic Forum in Davos, at the World Bank Distinguished Speaker Series and in the UK House of Commons. Edmans is heavily involved in the ongoing reform of corporate governance, in particular to ensure that both the diagnosis of problems and suggested solutions are based on rigorous evidence rather than anecdote. He was appointed by the UK government to study the effect of share buybacks on executive pay and investment. Edmans also serves on the Steering Group of The Purposeful Company, which aims to embed purpose into the heart of business, and on Royal London Asset Management's Responsible Investment Advisory Committee.
Edmans has been interviewed by Bloomberg, BBC, CNBC, CNN, ESPN, Fox, ITV, NPR, Reuters, Sky News and Sky Sports, and has written for the Wall Street Journal, Financial Times and Harvard Business Review. He runs a blog, Access to Finance, that makes academic research accessible to a general audience, and was appointed Mercers' School Memorial Professor of Business by Gresham College, to give free lectures to the public. Edmans was previously a tenured professor at Wharton, where he won 14 teaching awards in six years. At LBS, he won the Excellence in Teaching award, LBS's highest teaching accolade.
Alex Edmans | Speaker | TED.com