B1 中級 18 分類 收藏
開始影片後,點擊或框選字幕可以立即查詢單字
字庫載入中…
回報字幕錯誤
Some critics of the TV show Mythbusters claim
that the show misrepresents the scientific process.
For example, experiments are sometimes conducted only once
and without adequate controls,
but then these results are
generalized to make definitive claims
rather than repeating the experiment
and using statistical analysis as a scientist would
to figure out what is really true.
So, ironically a show
that is meant to educate people about science
may instead be giving them the opposite impression
of how science works.
But you know, similar criticisms had been made of Veritasium.
For example, when Destin and I performed
our experiments to show that the water swirls
the opposite way in the northern and southern hemispheres,
we only showed doing it once
even though we each did it three or four times in our own hemisphere.
And I guess that brings forth the question
should we change what we're doing --
I mean should Mythbusters and Veritasium
really show the repetitive nature of science
and use statistical results as evidence for our claims.
Well my answer is no, but to understand why
we first have to dig into something called
the helping experiment.
And this was performed in New York
in the 1960s. And the way it went was --
individual participants were placed in isolated booths
where they could speak to five other participants through an intercom
but only one mic was live at a time.
And these participants were meant to speak in turns
for two minutes each about their lives --
any problems they were having --
and it would just go in rounds.
Now what the participants didn't know was that
one of them was actually an actor
who was reading a script
prepared for him by the experimenters.
And he went first in the first round.
He talked about the problems he was having adjusting to life in New York City
and particularly the difficulty that he gets the seizures, particularly when stressed.
And so everyone else had their turn and then it came back 'round
to this actor again. Now this time
when he was speaking he became more and more incoherent as he
was talking. He said that he could feel a seizure coming on and he made choking noises,
he asked for help from the other participants --
he said he felt like he was dying --
and, uh, then he continued to get more and more distressed
until his mic went off.
And the point of the experiment was to see how many of the participants would help.
I mean, if you were one of the other participants, do you think you would've left your booth
and gone to see if he was okay?
In total, about 13 participants took part in this experiment --
and the number that helped before his mic was turned off --
was just four.
Now, while this might sound a little bit disappointing
about the state of human helpfulness,
you gotta keep in mind that there were other people listening to the same distress call
and that may have diffused the responsibility that individuals would feel;
this is something known as the "bystander effect."
Now, what's interesting about this experiment from my point of view
is not how it confirms the bystander effect,
but in how people view the results.
For example, they fail to change their opinion
of themselves or others after learning about this experiment.
For example, have you changed your opinion
about how likely you would be to help in this situation --
now that you know that only 30 percent of people did, in that situation?
Well, there was a follow-up study conducted
where students were shown two videos
of individual participants who were purported to be from the original study.
And they had already learned about the study,
and then they were asked at the end of watching those two videos --
which were pretty uninformative, just showed that these people were
good, decent, ordinary people --
these students were asked,
"How likely do you think it was
that those two particular participants helped?"
And overwhelmingly students felt
that those two participants would have helped --
even though they knew that, statistically, only 30 percent did, so,
in fact, if would've been a better guess to say that they probably didn't.
They didn't seem to really internalize
those general results as pertaining to the particular,
they kind of assumed it excluded
ordinary, good, decent people.
Now, is there a way to get people to really
understand how the world works?
Well, they did another follow-up study
where they talked about the experiment,
they described the experiment,
but they didn't give the results.
And then they showed those two participant videos --
again, not mentioning anything about the experiment,
just showing that these are two, decent, ordinary people
and then they told the students that those two people
did not help in the experiment.
And they asked the students to, uh, guess
what proportion of people did help.
And now, in this case, when they were going
from those particular examples of ordinary, nice people
who didn't help,
they were much better at generalizing
to the overall result,
to the statistical result.
In fact, they got it basically right.
And I think this highlights for us that
our brains are much better at
working with individual stories
and things in detail
than they are with statistical results.
And that is why I think
if you're Mythbusters or Veritasium
it's better to communicate science --
to tell the story,
to show the experiment, really, once in a dramatic way --
rather than three or four times
where each new iteration --
well, each repetition --
just confirms the original result that you were talking about.
But if you're actually doing the science.
If you're actually trying to establish scientific fact --
then of course
you need the repetition and the statistical analysis.
So I think it really does come down to what your objectives are.
But with this conclusion
I think this opens up
two big potential pitfalls.
One is that people without scientific evidence
can make crafty stories
that catch on
and quickly become what people feel is the truth.
And the other pitfall is scientists
Who have strong scientific evidence --
Who have clear statistical results --
and yet they can't communicate them to people
because they don't have a great story.
So, an example of the first pitfall
is the recent spread of this rumor
That the outbreak of a birth defect microsephaly
in South America was actually caused
by a larvicide made by Monsanto.
That story caught on like wildfire.
And you can see why because its got this clear villain --
that everyone loves to hate -- in Monsanto.
And its got a really causal story
That someone is doing something bad
to the water -- and its this poison
that were poisoning ourselves and
its a very emotive -- clear -- story.
While the other story is, uh,
Well it's a little bit more statistical -- that there is
some kind of connection -- which is the scientific consensus
That the Zika virus carried by
these, uh, mosquitoes
is causing the microsephaly.
And there are strong indications that that really is what's happening.
And if you look at the claims about the larvicide,
they really don't hold much weight.
I mean, the larvicide is so weak,
that you could drink a thousand litres of it a day.
A thousand litres of the water treated with this larvicide and have no adverse effects.
Or, uh, this larvicide has been used in dog and cat pet collars.
Um, so really, you know, there isn't strong evidence for the larvicide connection. In fact
There is no connection between the larvicide and Monsanto at all.
But I think the story took hold because it had such a strong narrative
On the other hand, you have things like climate change,
which have very strong statistical evidence to back them up,
large scale result over the globe.
And yet, one cold snowy winter is so much more, uh,
visceral and meaningful to individual people
than this thing which feels, you know,
completely databased.
And, it just depends on how much you trust data, I guess.
As scientists, we love data.
And we feel like, if we're trying to communicate to someone,
we're trying to convince someone of something,
all we have to do is show more data.
But what experiments demonstrate to us with statistical certainty
is that stories work much better.
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.
提示:點選文章或是影片下面的字幕單字,可以直接快速翻譯喔!

載入中…

Why Anecdotes Trump Data

18 分類 收藏
林宜悉 發佈於 2020 年 3 月 29 日
看更多推薦影片
  1. 1. 單字查詢

    在字幕上選取單字即可即時查詢單字喔!

  2. 2. 單句重複播放

    可重複聽取一句單句,加強聽力!

  3. 3. 使用快速鍵

    使用影片快速鍵,讓學習更有效率!

  4. 4. 關閉語言字幕

    進階版練習可關閉字幕純聽英文哦!

  5. 5. 內嵌播放器

    可以將英文字幕學習播放器內嵌到部落格等地方喔

  6. 6. 展開播放器

    可隱藏右方全文及字典欄位,觀看影片更舒適!

  1. 英文聽力測驗

    挑戰字幕英文聽力測驗!

  1. 點擊展開筆記本讓你看的更舒服

  1. UrbanDictionary 俚語字典整合查詢。一般字典查詢不到你滿意的解譯,不妨使用「俚語字典」,或許會讓你有滿意的答案喔