that the show misrepresents the scientific process.

這個節目扭曲了科學過程

For example, experiments are sometimes conducted only once

舉例來說，實驗有時候只進行一次

and without adequate controls,

而且沒有足夠的控制

but then these results are

而用這樣的(實驗)結果

generalized to make definitive claims

推導出確定的結論

rather than repeating the experiment

作為一個科學家，沒有反覆的實驗也沒有統計分析

and using statistical analysis as a scientist would

作為一個科學家，沒有反覆的實驗也沒有統計分析

to figure out what is really true.

來確認什麼是真的事實

So, ironically a show

諷刺的是，這個為了讓人們更了解科學的節目

that is meant to educate people about science

諷刺的是，這個為了讓人們更了解科學的節目

may instead be giving them the opposite impression

帶給人們(對科學)並不科學的印象

of how science works.

帶給人們(對科學)並不科學的印象

But you know, similar criticisms had been made of Veritasium.

但你知道，Veritasium表示了類似的批評

For example, when Destin and I performed

舉例來說，當我與Destin進行我們的實驗

our experiments to show that the water swirls

展示漩渦在北半球與南半球方向會相反

the opposite way in the northern and southern hemispheres,

展示漩渦在北半球與南半球方向會相反

we only showed doing it once

我們只展示一次

even though we each did it three or four times in our own hemisphere.

雖然我們各自(負責的)(南北)半球都做了三四次

And I guess that brings forth the question

我想這帶來了個問題

should we change what we're doing --

是否我們該改變我們的做法？

I mean should Mythbusters and Veritasium

我的意思是，流言終結者 與 Veritasium 是否應該

really show the repetitive nature of science

真正展示重複的自然科學與統計結果

and use statistical results as evidence for our claims.

來提供我們所宣稱的科學證據？

Well my answer is no, but to understand why

我的答案是不，但要了解為何是不

we first have to dig into something called

我們首先要深入探討什麼是所謂的

the helping experiment.

(對人們)有幫助的實驗

And this was performed in New York

1960年代在紐約進行了一場實驗。

in the 1960s. And the way it went was --

實驗進行的方式是將

individual participants were placed in isolated booths

個人參與者安排在隔離的攤位裡

where they could speak to five other participants through an intercom

他們可以利用對講機對其他五名參與者說話

but only one mic was live at a time.

但每一次只有一個麥克風是有作用的

And these participants were meant to speak in turns

原意是要讓這些參與者輪流說話

for two minutes each about their lives --

每個人有2分鐘可以講他們的生活

any problems they were having --

以及他們所遭遇的問題

and it would just go in rounds.

而且這會以回合制進行。

Now what the participants didn't know was that

當時參與者們所不知道的是

one of them was actually an actor

他們其中的一個人其實是演員

who was reading a script

單純只是讀著實驗者所準備給他的稿子演出

prepared for him by the experimenters.

單純只是讀著實驗者所準備給他的稿子演出

And he went first in the first round.

這個人又是在第一回合中的第一個發言

He talked about the problems he was having adjusting to life in New York City

他講述著他為了適應紐約市的生活所面臨的問題

and particularly the difficulty that he gets the seizures, particularly when stressed.

特別是因為在壓力下易犯癲癇所帶來的困難處

And so everyone else had their turn and then it came back 'round

接下來每個人依序輪流發言

to this actor again. Now this time

等到又輪回到這個演員時

when he was speaking he became more and more incoherent as he

這次他的發言內容變得愈來愈顛三倒四

was talking. He said that he could feel a seizure coming on and he made choking noises,

他告訴大家他有癲癇即將發作的預感，然後發出快要窒息的聲音

he asked for help from the other participants --

他向其他的參與者求助

he said he felt like he was dying --

他說他感覺好像快要死了

and, uh, then he continued to get more and more distressed

他繼續表現得愈來愈痛苦

until his mic went off.

直到他的麥克風被消音為止

And the point of the experiment was to see how many of the participants would help.

這個實驗的目的在於觀察有多少參與者會挺身而出

I mean, if you were one of the other participants, do you think you would've left your booth

如果你是這其他的參與者之一，你想你會離開你的攤位去看看他的情況？

and gone to see if he was okay?

如果你是這其他的參與者之一，你想你會離開你的攤位去看看他的情況？

In total, about 13 participants took part in this experiment --

總共約有13人參與了這個實驗

and the number that helped before his mic was turned off --

在麥克風消音之前，願意伸出援手的只有4個人

was just four.

在麥克風消音之前，願意伸出援手的只有4個人

Now, while this might sound a little bit disappointing

這個實驗結果令人對於人類的助人天性

about the state of human helpfulness,

不敢寄予厚望

you gotta keep in mind that there were other people listening to the same distress call

別忘了當時還有其他人都聽到了同樣的呼救

and that may have diffused the responsibility that individuals would feel;

那會使得每個人都覺得自己不是唯一要負起責任的人

this is something known as the "bystander effect."

這就是所謂的"旁觀者效應"

Now, what's interesting about this experiment from my point of view

從我的角度來看，這個實驗有趣的地方

is not how it confirms the bystander effect,

不是在於它如何確認了旁觀者效應

but in how people view the results.

而是人們如何看待它的結果

For example, they fail to change their opinion

舉例說，人們並沒有因為這個實驗

of themselves or others after learning about this experiment.

而改變對自己或對他人的看法

For example, have you changed your opinion

比如說，你會對於自己在這種情況下伸出援手的可能性作出改變嗎？

about how likely you would be to help in this situation --

比如說，你會對於自己在這種情況下伸出援手的可能性作出改變嗎？

now that you know that only 30 percent of people did, in that situation?

當你得知在這情況下只有30%的人會這麼做時

Well, there was a follow-up study conducted

這還曾經有個後續的研究

where students were shown two videos

進行方法是將2個影片播放給學生們看

of individual participants who were purported to be from the original study.

並聲稱影片中的個人參與者來自於最初始的研究

And they had already learned about the study,

學生們對於那場實驗的細節均了然於胸

and then they were asked at the end of watching those two videos --

然後在看完這兩段影片後向學生們提問

which were pretty uninformative, just showed that these people were

其實影片中並沒有提供什麼太多信息，只是顯示這些參與者是

good, decent, ordinary people --

好人，正經人，普通人

these students were asked,

當這些學生被問到

"How likely do you think it was

"你認為影片中這兩名參與者在實驗中伸出援手的可能性有多大？"

that those two particular participants helped?"

"你認為影片中這兩名參與者在實驗中伸出援手的可能性有多大？"

And overwhelmingly students felt

學生們一面倒地認為

that those two participants would have helped --

這兩名參與者都會伸出援手

even though they knew that, statistically, only 30 percent did, so,

即使他們已知曉，統計上只有30%的人會

in fact, if would've been a better guess to say that they probably didn't.

事實上說他們不會幫忙，反而猜中機率較高

They didn't seem to really internalize

學生們似乎並沒有把先前一般性實驗結果吸收內化然後關連運用到特定取樣測試

those general results as pertaining to the particular,

學生們似乎並沒有把先前一般性實驗結果吸收內化然後關連運用到特定取樣測試

they kind of assumed it excluded

他們就假設它已排除了普通人，好人和正經人

ordinary, good, decent people.

他們就假設它已排除了普通人，好人和正經人

Now, is there a way to get people to really

有沒有什麼方法可以讓人們

understand how the world works?

真正地瞭解這個世界是如何運作？

Well, they did another follow-up study

他們又做了另一個後續研究

where they talked about the experiment,

再次談及到那一場實驗

they described the experiment,

他們描述了實驗的細節

but they didn't give the results.

但卻不提供實驗的結果

And then they showed those two participant videos --

然後他們播放了這兩名參與者的影片

again, not mentioning anything about the experiment,

一樣，不再提醒實驗中的任何事情

just showing that these are two, decent, ordinary people

只是給他們看這兩名看起來正經而普通的人

and then they told the students that those two people

然後他們告訴這些學生們

did not help in the experiment.

這兩個人在實驗中都沒有伸出援手

And they asked the students to, uh, guess

他們再讓這些學生去猜

what proportion of people did help.

有多少比例的人伸出了援手

And now, in this case, when they were going

在這個案例中，當他們得知從那些普通好人中的具體例子並沒有伸出援手

from those particular examples of ordinary, nice people

在這個案例中，當他們得知從那些普通好人中的具體例子並沒有伸出援手

who didn't help,

在這個案例中，當他們得知從那些普通好人中的具體例子並沒有伸出援手

they were much better at generalizing

他們在將總體實驗結果泛化去推測統計結果的表現就好得多了

to the overall result,

他們在將總體實驗結果泛化去推測統計結果的表現就好得多了

to the statistical result.

他們在將總體實驗結果泛化去推測統計結果的表現就好得多了

In fact, they got it basically right.

他們基本上都是對的

And I think this highlights for us that

我認為這其中的亮點是

our brains are much better at

我們的大腦相對於統計結果，

working with individual stories

其實更擅長於處理個別的故事以及有細節的事情

and things in detail

其實更擅長於處理個別的故事以及有細節的事情

than they are with statistical results.

其實更擅長於處理個別的故事以及有細節的事情

And that is why I think

這就是為什麼我認為

if you're Mythbusters or Veritasium

如果你是 流言終結者 或是Veritasium的話

it's better to communicate science --

要去講故事以及傳達科學理念

to tell the story,

要去講故事以及傳達科學理念

to show the experiment, really, once in a dramatic way --

用戲劇性的方式展示一次實驗會優於

rather than three or four times

三到四次一再迭代且重覆的實驗

where each new iteration --

三到四次一再迭代且重覆的實驗

well, each repetition --

三到四次一再迭代且重覆的實驗

just confirms the original result that you were talking about.

只為了確認你想談及的初始結果

But if you're actually doing the science.

但如果你是真的在做科學研究

If you're actually trying to establish scientific fact --

如果你是真的想要建立科學事證

then of course

那麼當然

you need the repetition and the statistical analysis.

你需要重覆實驗和統計分析

So I think it really does come down to what your objectives are.

所以我認為那基本上要看你的目標是什麼？

But with this conclusion

這個結論

I think this opens up

我想又打開了

two big potential pitfalls.

兩個潛在的大陷阱

One is that people without scientific evidence

其一是人們沒有科學證據

can make crafty stories

就編造出會被瘋傳的詭詐故事

that catch on

並且很快地讓人們把自己的感覺當成事實

and quickly become what people feel is the truth.

並且很快地讓人們把自己的感覺當成事實

And the other pitfall is scientists

另一個陷阱是科學家們

Who have strong scientific evidence --

擁有很紮實的科學證據

Who have clear statistical results --

有些很清晰的統計結果

and yet they can't communicate them to people

但他們卻無法與一般民眾對談科學

because they don't have a great story.

因為他們沒有一個神奇的故事

So, an example of the first pitfall

第一個陷阱的一個事例

is the recent spread of this rumor

就是最近流傳的一則謠言

That the outbreak of a birth defect microsephaly

南美洲爆發的嬰兒小頭症，

in South America was actually caused

實際上是由孟山都公司製造的殺蟎劑所造成的

by a larvicide made by Monsanto.

實際上是由孟山都公司製造的殺蟎劑所造成的

That story caught on like wildfire.

這個說法就像野火燎原般被瘋傳

And you can see why because its got this clear villain --

其中很大的原因是它立起了一個清楚又眾人嫌惡的稻草人公敵 -- 孟山都公司

that everyone loves to hate -- in Monsanto.

其中很大的原因是它立起了一個清楚又眾人嫌惡的稻草人公敵 -- 孟山都公司

And its got a really causal story

這個故事中完美交代因果關係

That someone is doing something bad

某人對水源做了一些壞事

to the water -- and its this poison

使它變成毒水

that were poisoning ourselves and

毒水使人們中毒

its a very emotive -- clear -- story.

這是非常煽動的故事

While the other story is, uh,

另一個故事是

Well it's a little bit more statistical -- that there is

這個有牽涉到一點統計學，

some kind of connection -- which is the scientific consensus

根據統計結果證明的關連性所形成的科學共識是

That the Zika virus carried by

病媒蚊攜帶的茲卡病毒

these, uh, mosquitoes

病媒蚊攜帶的茲卡病毒

is causing the microsephaly.

才是導致嬰兒小頭症的病因

And there are strong indications that that really is what's happening.

這個故事有著強而有力的事證說明了來龍去脈

And if you look at the claims about the larvicide,

而且如果你去看那些關於殺蟎劑的宣稱

they really don't hold much weight.

其實證據都很薄弱

I mean, the larvicide is so weak,

我的意思是，殺蟎劑根本算不上有毒

that you could drink a thousand litres of it a day.

你一天喝1000公升都不會有事

A thousand litres of the water treated with this larvicide and have no adverse effects.

1000公升含有殺蟎劑的水也不會有任何不良效果

Or, uh, this larvicide has been used in dog and cat pet collars.

這些殺蟎劑也被應用在貓狗用的除蟲項圈

Um, so really, you know, there isn't strong evidence for the larvicide connection. In fact

事實上沒有很紮實的證據指示指出殺蟎劑與小頭症有任何關連

There is no connection between the larvicide and Monsanto at all.

殺蟎劑與孟山都公司之間也沒有什麼瓜葛

But I think the story took hold because it had such a strong narrative

但是我認為這個故事是有把柄的，因為它有如此強烈的敘述

On the other hand, you have things like climate change,

在另一方面有像氣候變遷的案例

which have very strong statistical evidence to back them up,

它有著堅強的統計證據支持

large scale result over the globe.

還有來自全球各地大規模的數據結果

And yet, one cold snowy winter is so much more, uh,

但是一個寒冷暴雪的冬天對於個人而言比來自數據資料庫更加有溫度感和意義

visceral and meaningful to individual people

但是一個寒冷暴雪的冬天對於個人而言比來自數據資料庫更加有溫度感和意義

than this thing which feels, you know,

但是一個寒冷暴雪的冬天對於個人而言比來自數據資料庫更加有溫度感和意義

completely databased.

但是一個寒冷暴雪的冬天對於個人而言比來自數據資料庫更加有溫度感和意義

And, it just depends on how much you trust data, I guess.

我想，這取決於你有多麼信任數據

As scientists, we love data.

身為科學家，我們愛死數據了

And we feel like, if we're trying to communicate to someone,

我們的感覺是，如果要去和某人溝通對話

we're trying to convince someone of something,

如果要在某件事上去說服某人

all we have to do is show more data.

我們要做的就是拿出更多資料數據

But what experiments demonstrate to us with statistical certainty

但是那個實驗以統計確定性告訴我們的則是

is that stories work much better.

要說服人，講故事才是更為有效的方法

Normally I do this walk and talk self videos on my second channel, 2Veritasium, but

I imagine that some of you might not know that that exists.

So, I thought I'd put one of these here on 1Veritasium.

Plus, this one has a fair amount of data and, you know, experimental stuff in it,

so I figured that could be interesting for you as well.

So if you want to check out the check...

[CHUCKLES]

So if you want to check out the second channel, then

go to 2Veritasium. I'll put a card or something for it up here.