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.