0:00:01.830,0:00:04.268
Every day we face issues like climate change

0:00:04.268,0:00:05.708
or the safety of vaccines

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where we have to answer questions whose answers

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rely heavily on scientific information.

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Scientists tell us that the world is warming.

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Scientists tell us that vaccines are safe.

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But how do we know if they are right?

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Why should be believe the science?

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

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Public opinion polls consistently show

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that significant proportions of the American people

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

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

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and aren't persuaded by the safety of vaccines.

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So why should we believe the science?

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

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In fact, they would contract science with faith,

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and they would say belief is the domain of faith.

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

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Indeed they would say religion is based on faith

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or maybe the calculous of Pascal's wager.

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Blaise Pascal was a 17th century mathematician

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who tried to bring scientific[br]reasoning to the question of

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whether or not he should believe in God,

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and his wager went like this:

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well, if God doesn't exist

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but I decide to believe in him

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nothing much is really lost.

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Maybe a few hours on Sunday.

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[Laughter]

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

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then I'm in deep trouble.

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

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Or as one of my college professors said,

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"He clutched for the handmill of faith."

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He made that leap of faith

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leaving science and rationalism behind.

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Now the fact is though, for most of us,

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most scientific claims are a leap of faith.

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

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And indeed this is actually[br]true for most scientists as well

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outside of their own specialties.

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

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whether a vaccine is safe.

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Most chemists are not experts in evolutionary theory.

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A physicist cannot tell you,

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despite the claims of some of them,

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whether or not tobacco causes cancer.

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So, if even scientists themselves

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have to make a leap of faith

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outside their own fields,

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then why do they accept the[br]claims of other scientists?

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Why do they believe each other's claims?

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And should we believe those claims?

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

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but not for the reason that most of us think.

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

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believe in science is because of the scientific method.

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We were taught that scientists follow a method

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and that this method guarantees

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the truth of their claims.

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The method that most of us were taught in school,

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we can call it the text book method,

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is the hypothetical deductive method.

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According to the standard[br]model, the textbook model,

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scientists develop hypotheses, they deduce

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the consequences for those hypotheses,

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

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"Okay, well are those consequences true?"

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Can we observe them taking[br]place in the natural world?

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And if they are true, then the scientists say,

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"Great, we know the hypothesis is correct."

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So there are many famous examples in the history

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of science of scientists doing exactly this.

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One of the most famous examples

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comes from the work of Albert Einstein.

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When Einstein developed the[br]theory of general relativity,

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one of the consequences of his theory

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was that space time wasn't just an empty void

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but that it actually had a fabric.

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And that that fabric was bent

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in the presence of massive objects like the sun.

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So if this theory were true then it meant that light

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as it passed the sun

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should actually be bent around it.

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That was a pretty startling prediction

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and it took a few years before scientists

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were able to test it.

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But they did test it in 1919,

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and lo and behold it turned out to be true.

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Starlight actually does bend[br]as it travels around the sun.

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This was a huge confirmation of the theory.

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It was considered proof of the truth

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of this radical new idea,

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and it was written up in many newspapers

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around the globe.

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Now sometimes this theory or this model

0:04:11.850,0:04:14.874
is referred to as the deductive-nomological model.

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Meaning those academics[br]like to make things complicated.

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

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So nomological means having to do with laws.

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

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ideally, it is a law of nature.

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

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

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

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in all times and all places

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no matter what the circumstances are.

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

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Einstein's famous equation, E=MC2,

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which tells us what the relationship is

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between energy and mass.

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And that relationship is true no matter what.

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

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The main problem is that it's wrong.

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It's just not true. [Laughter]

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

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So the first reason is a logical reason.

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It's the problem of the fallacy[br]of affirming the consequent.

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So that's another fancy academic way of saying

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that false theories can make true predictions.

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So just because the prediction comes true

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

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

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This is a picture of the Ptolemaic universe

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with the Earth at the center of the universe

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and The Sun and the planets going around it.

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The Ptolemaic model was believed

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by many very smart people for many centuries.

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Well, why?

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

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The Ptolemaic system enabled astronomers

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to make accurate predictions[br]of the motions of the planet,

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in fact more accurate predictions at first

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

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So that's one problem with the textbook model.

0:06:03.867,0:06:06.353
A second problem is a practical problem,

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and it's the problem of auxiliary hypotheses.

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Auxiliary hypotheses are assumptions

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that scientists are making

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

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So an important example of this

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comes from the Copernican model,

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which ultimately replaced the Ptolemaic system.

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So when Nicolaus Copernicus said,

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actually the Earth is not the center of the universe,

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the sun is the center of the solar system,

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the Earth moves around the sun.

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

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we ought to be able to detect the motion

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of the Earth around the sun.

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And so this slide here illustrates a concept

0:06:42.803,0:06:44.731
known as stellar parallax.

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And astronomers said, if the Earth is moving

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

0:06:51.763,0:06:53.747
—well I know I'm in Manhattan[br]so you guys can't see the stars,

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

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

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against the backdrop of distant stars.

0:07:03.610,0:07:06.474
If we now make the same observation six months later

0:07:06.474,0:07:09.986
when the Earth has moved to this position in June,

0:07:09.986,0:07:14.275
we look at that same star and we see it against a different backdrop.

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That difference, that angular[br]difference, is the stellar parallax.

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So this is the prediction that[br]the Copernican model makes.

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Astronomers looked for the stellar parallax

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and they found nothing, nothing at all.

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

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So what happened?

0:07:34.507,0:07:37.100
Well in hindsight we can say that astronomers were making

0:07:37.100,0:07:39.427
two auxiliary hypotheses, both of which

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we would now say were incorrect.

0:07:42.069,0:07:45.635
The first was an assumption about the size of the Earth's orbit.

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Astronomers were assuming that the Earth's orbit was large

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relative to the distance of the stars.

0:07:51.259,0:07:53.723
Today we would draw the picture more like this,

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this comes from NASA,

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

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

0:08:00.604,0:08:01.933
The stellar parallax therefore,

0:08:01.933,0:08:05.637
is very small and actually very hard to detect.

0:08:05.637,0:08:07.421
And that leads to the second reason

0:08:07.421,0:08:09.093
why the prediction didn't work,

0:08:09.093,0:08:11.325
because scientists were also assuming

0:08:11.325,0:08:14.365
that the telescopes they had were sensitive enough

0:08:14.365,0:08:16.245
to detect the parallax.

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And that turned out not to be true.

0:08:18.412,0:08:20.376
It wasn't until the 19th century

0:08:20.376,0:08:22.048
that scientists were able to detect

0:08:22.048,0:08:24.156
the stellar parallax.

0:08:24.156,0:08:26.792
So, there's a third problem as well.

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The third problem is simply a factual problem,

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

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A lot of science isn't deductive at all,

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it's actually inductive.

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And by that we mean that scientists don't necessarily

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start with theories and hypotheses, often they just

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start with observations of stuff going on in the world.

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And the most famous example[br]of that is one of the most

0:08:47.602,0:08:50.767
famous scientists who ever lived, Charles Darwin.

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

0:08:53.759,0:08:57.431
he didn't have a hypothesis, he didn't have a theory.

0:08:57.431,0:09:00.687
He just knew that he wanted[br]to have a career as a scientist

0:09:00.687,0:09:02.739
and he started to collect data.

0:09:02.739,0:09:04.699
Mainly he knew that he hated medicine

0:09:04.699,0:09:06.987
because the sight of blood made him sick so

0:09:06.987,0:09:09.395
he had to have an alternative career path.

0:09:09.395,0:09:11.499
So he started collecting data.

0:09:11.499,0:09:14.635
And he collected many things including his famous finches.

0:09:14.635,0:09:16.915
When he collected these finches,[br]he threw them in a bag

0:09:16.915,0:09:19.525
and he had no idea what they meant.

0:09:19.525,0:09:21.412
Many years later back in London,

0:09:21.412,0:09:23.625
Darwin looked at his data again and began

0:09:23.625,0:09:26.113
to develop an explanation,

0:09:26.113,0:09:29.561
and that explanation was the[br]theory of natural selection.

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Besides inductive science,

0:09:31.390,0:09:34.576
scientists also often participate in modeling.

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One of the things scientists want to do in life

0:09:36.872,0:09:39.063
is to explain the causes of things.

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And how do we do that?

0:09:40.848,0:09:43.071
Well, one way you can do it is to build a model

0:09:43.071,0:09:44.872
that tests an idea.

0:09:44.872,0:09:46.663
So this is a picture of Henry Cadell,

0:09:46.663,0:09:49.119
who was a Scottish geologist in the 19th century.

0:09:49.119,0:09:50.912
You can tell he's Scottish because he's wearing

0:09:50.912,0:09:53.064
a deerstalker cap and Wellington boots.

0:09:53.064,0:09:55.304
[Laughter]

0:09:55.304,0:09:57.061
And Cadell wanted to answer the question,

0:09:57.061,0:09:58.748
how are mountains formed?

0:09:58.748,0:10:00.244
And one of the things he had observed

0:10:00.244,0:10:02.908
is that if you look at mountains[br]like the Appalachians,

0:10:02.908,0:10:04.741
you often find that the rocks in them

0:10:04.741,0:10:06.060
are folded,

0:10:06.060,0:10:07.636
and they're folded in a particular way,

0:10:07.636,0:10:09.020
which suggested to him

0:10:09.020,0:10:11.969
that they were actually being[br]compressed from the side.

0:10:11.969,0:10:14.157
And this idea would later play a major role

0:10:14.157,0:10:16.500
in discussions of continental drift.

0:10:16.500,0:10:18.956
So he built this model, this crazy contraption

0:10:18.956,0:10:21.268
with levers and wood and here's his wheelbarrow,

0:10:21.268,0:10:23.044
buckets, a big sledgehammer.

0:10:23.044,0:10:25.388
I don't know why he's got the Wellington boots.

0:10:25.388,0:10:27.165
Maybe it's going to rain.

0:10:27.165,0:10:30.012
And he created this physical model in order

0:10:30.012,0:10:34.525
to demonstrate that you could in fact create

0:10:34.525,0:10:37.139
patterns in rocks, or at least in this case in mud,

0:10:37.139,0:10:39.275
that looked a lot like mountains

0:10:39.275,0:10:41.107
if you compressed them from the side.

0:10:41.107,0:10:44.475
So it was an argument about[br]the cause of mountains.

0:10:44.475,0:10:47.443
Nowadays, most scientists prefer to work inside,

0:10:47.443,0:10:50.043
so they don't build physical models so much

0:10:50.043,0:10:52.371
as to make computer simulations.

0:10:52.371,0:10:55.099
But a computer simulation is a kind of a model.

0:10:55.099,0:10:57.243
It's a model that's made with mathematics,

0:10:57.243,0:10:59.876
and like the physical models of the 19th century,

0:10:59.876,0:11:03.974
it's very important for thinking about causes.

0:11:03.974,0:11:06.509
So one of the big questions[br]to do with climate change,

0:11:06.509,0:11:08.372
we have tremendous amounts of evidence

0:11:08.372,0:11:10.412
that the earth is warming up.

0:11:10.412,0:11:12.636
This slide here, the black line shows

0:11:12.636,0:11:14.756
the measurements that scientists have taken

0:11:14.756,0:11:16.899
for the last 150 years

0:11:16.899,0:11:18.299
showing that the earth's temperature

0:11:18.299,0:11:19.923
has steadily increased,

0:11:19.923,0:11:22.829
and you can see in particular[br]that in the last 50 years

0:11:22.829,0:11:24.683
there's been this dramatic increase

0:11:24.683,0:11:26.843
of nearly one degree Centigrade,

0:11:26.843,0:11:29.188
or almost two degrees Fahrenheit.

0:11:29.188,0:11:31.835
So what, though, is driving that change?

0:11:31.835,0:11:34.052
How can we know what's causing

0:11:34.052,0:11:35.756
the observed warming?

0:11:35.756,0:11:37.300
Well, scientists can model it

0:11:37.300,0:11:39.428
using a computer simulation.

0:11:39.428,0:11:42.380
So this diagram illustrates a computer simulation

0:11:42.380,0:11:44.491
that has looked at all the different factors

0:11:44.491,0:11:46.756
that we know can influence the earth's climate,

0:11:46.756,0:11:49.668
so sulfate particles from air pollution,

0:11:49.668,0:11:53.188
volcanic dust from volcanic eruptions,

0:11:53.188,0:11:54.932
changes in solar radiation,

0:11:54.932,0:11:57.590
and, of course, greenhouse gases.

0:11:57.590,0:11:59.148
And they asked the question,

0:11:59.148,0:12:02.604
what set of variables put into a model

0:12:02.604,0:12:06.076
will reproduce what we actually see in real life?

0:12:06.076,0:12:08.180
So here is the real life in black.

0:12:08.180,0:12:10.290
Here's the model in this light grey,

0:12:10.290,0:12:12.011
and the answer is

0:12:12.011,0:12:16.287
a model that includes, it's the answer E on that SAT,

0:12:16.287,0:12:18.548
all of the above.

0:12:18.548,0:12:20.164
The only way you can reproduce

0:12:20.164,0:12:21.812
the observed temperature measurements

0:12:21.812,0:12:23.900
is with all of these things put together,

0:12:23.900,0:12:25.979
including greenhouse gases,

0:12:25.979,0:12:28.059
and in particular you can see that the increase

0:12:28.059,0:12:29.964
in greenhouse gases tracks

0:12:29.964,0:12:32.084
this very dramatic increase in temperature

0:12:32.084,0:12:34.019
over the last 50 years.

0:12:34.019,0:12:36.484
And so this is why climate scientists say

0:12:36.484,0:12:39.332
it's not just that we know that[br]climate change is happening,

0:12:39.332,0:12:42.220
we know that greenhouse gases are a major part

0:12:42.220,0:12:45.068
of the reason why.

0:12:45.068,0:12:47.228
So now because there all these different things

0:12:47.228,0:12:48.847
that scientists do,

0:12:48.847,0:12:51.823
the philosopher Paul Feyerabend famously said,

0:12:51.823,0:12:53.799
"The only principle in science

0:12:53.799,0:12:57.998
that doesn't inhibit progress is: anything goes."

0:12:57.998,0:13:00.654
Now this quotation has often[br]been taken out of context,

0:13:00.654,0:13:02.742
because Feyerabend was not actually saying

0:13:02.742,0:13:04.342
that in science anything goes.

0:13:04.342,0:13:06.126
What he was saying was,

0:13:06.126,0:13:08.014
actually the full quotation is,

0:13:08.014,0:13:10.023
"If you press me to say

0:13:10.023,0:13:11.766
what is the method of science,

0:13:11.766,0:13:15.455
I would have to say: anything goes."

0:13:15.455,0:13:16.703
What he was trying to say

0:13:16.703,0:13:19.037
is that scientists do a lot of different things.

0:13:19.037,0:13:21.478
Scientists are creative.

0:13:21.478,0:13:23.758
But then this pushes the question back:

0:13:23.758,0:13:26.599
if scientists don't use a single method,

0:13:26.599,0:13:28.758
then how do they decide

0:13:28.758,0:13:30.406
what's right and what's wrong?

0:13:30.406,0:13:32.099
And who judges?

0:13:32.099,0:13:34.078
And the answer is, scientists judge,

0:13:34.078,0:13:37.303
and they judge by judging evidence.

0:13:37.303,0:13:40.302
Scientists collect evidence in many different ways,

0:13:40.302,0:13:42.374
but however they collect it,

0:13:42.374,0:13:44.921
they have to subject it to scrutiny.

0:13:44.921,0:13:47.231
And this led to sociologist Robert Merton

0:13:47.231,0:13:49.551
to focus on this question of how scientists

0:13:49.551,0:13:51.390
scrutinize data and evidence,

0:13:51.390,0:13:53.798
and he said they do it in a way he called

0:13:53.798,0:13:55.967
"organized skepticism."

0:13:55.967,0:13:57.801
And by that he meant it's organized

0:13:57.801,0:13:59.519
because they do it collectively,

0:13:59.519,0:14:01.238
they do it as a group,

0:14:01.238,0:14:03.774
and skepticism, because they do it from a position

0:14:03.774,0:14:05.318
of distrust.

0:14:05.318,0:14:07.038
That is to say, the burden of proof

0:14:07.038,0:14:09.701
is on the person with a novel claim.

0:14:09.701,0:14:12.914
And in this sense, science[br]is intrinsically conservative.

0:14:12.914,0:14:15.406
It's quite hard to persuade the scientific community

0:14:15.406,0:14:19.187
to say, "Yes, we know something, this is true."

0:14:19.187,0:14:21.443
So despite the popularity of the concept

0:14:21.443,0:14:23.092
of paradigm shifts,

0:14:23.092,0:14:24.454
what we find is that actually,

0:14:24.454,0:14:26.699
really major changes in scientific thinking

0:14:26.699,0:14:31.119
are relatively rare in the history of science.

0:14:31.119,0:14:34.642
So finally that brings us to one more idea:

0:14:34.642,0:14:38.460
if scientists judge evidence collectively,

0:14:38.460,0:14:40.972
this has led historians to focus on the question

0:14:40.972,0:14:42.461
of consensus,

0:14:42.461,0:14:44.226
and to say that at the end of the day,

0:14:44.226,0:14:46.061
what science is,

0:14:46.061,0:14:47.820
what scientific knowledge is,

0:14:47.820,0:14:51.119
is the consensus of the scientific experts

0:14:51.119,0:14:53.473
who through this process of organized scrutiny,

0:14:53.473,0:14:55.208
collective scrutiny,

0:14:55.208,0:14:56.970
have judged the evidence

0:14:56.970,0:14:59.577
and come to a conclusion about it,

0:14:59.577,0:15:02.234
either yea or nay.

0:15:02.234,0:15:03.858
So we can think of scientific knowledge

0:15:03.858,0:15:05.890
as a consensus of experts.

0:15:05.890,0:15:07.482
We can also think of science as being

0:15:07.482,0:15:09.290
a kind of a jury,

0:15:09.290,0:15:11.714
except it's a very special kind of jury.

0:15:11.714,0:15:13.618
It's not a jury of your peers,

0:15:13.618,0:15:16.184
it's a jury of geeks.

0:15:16.184,0:15:19.538
It's a jury of men and women with Ph.Ds,

0:15:19.538,0:15:21.730
and unlike a conventional jury,

0:15:21.730,0:15:23.540
which has only two choices,

0:15:23.540,0:15:25.895
guilty or not guilty,

0:15:25.895,0:15:29.466
the scientific jury actually has a number of choices.

0:15:29.466,0:15:32.095
Scientists can say yes, something's true.

0:15:32.095,0:15:35.078
Scientists can say no, it's false.

0:15:35.078,0:15:37.310
Or, they can say, well it might be true

0:15:37.310,0:15:40.324
but we need to work more[br]and collect more evidence.

0:15:40.324,0:15:42.012
Or, they can say it might be true,

0:15:42.012,0:15:43.650
but we don't know how to answer the question

0:15:43.650,0:15:45.027
and we're going to put it aside

0:15:45.027,0:15:47.883
and maybe we'll come back to it later.

0:15:47.883,0:15:51.915
That's what scientists call "intractable."

0:15:51.915,0:15:54.811
But this leads us to one final problem:

0:15:54.811,0:15:57.299
if science is what scientists say it is,

0:15:57.299,0:16:00.085
then isn't that just an appeal to authority?

0:16:00.085,0:16:01.352
And weren't we all taught in school

0:16:01.352,0:16:04.459
that the appeal to authority is a logical fallacy?

0:16:04.459,0:16:07.371
Well, here's the paradox of modern science,

0:16:07.371,0:16:09.603
the paradox of the conclusions I think historians

0:16:09.603,0:16:12.484
and philosophers and sociologists have come to,

0:16:12.484,0:16:15.675
that actually science is the appeal to authority,

0:16:15.675,0:16:19.511
but it's not the authority of the individual,

0:16:19.511,0:16:21.920
no matter how smart that individual is,

0:16:21.920,0:16:25.655
like Plato or Socrates or Einstein.

0:16:25.655,0:16:28.659
It's the authority of the collective community.

0:16:28.659,0:16:31.835
You can think of it is a kind of wisdom of the crowd,

0:16:31.835,0:16:35.291
but a very special kind of crowd.

0:16:35.291,0:16:37.651
Science does appeal to authority,

0:16:37.651,0:16:40.191
but it's not based on any individual,

0:16:40.191,0:16:42.547
no matter how smart that individual may be.

0:16:42.547,0:16:44.528
It's based on the collective wisdom,

0:16:44.528,0:16:47.037
the collective knowledge, the collective work,

0:16:47.037,0:16:48.768
of all of the scientists who have worked

0:16:48.768,0:16:51.595
on a particular problem.

0:16:51.595,0:16:54.571
Scientists have a kind of culture of collective distrust,

0:16:54.571,0:16:56.331
this "show me" culture,

0:16:56.331,0:16:58.331
illustrated by this nice woman here

0:16:58.331,0:17:01.283
showing her colleagues her evidence.

0:17:01.283,0:17:03.510
Of course, these people don't[br]really look like scientists,

0:17:03.510,0:17:05.746
because they're much too happy.

0:17:05.746,0:17:09.618
[Laughter]

0:17:09.618,0:17:13.066
Okay, so that brings me to my final point.

0:17:13.066,0:17:16.338
Most of us get up in the morning.

0:17:16.338,0:17:17.978
Most of us trust our cars.

0:17:17.978,0:17:19.450
Well, see, now I'm thinking, I'm in Manhattan,

0:17:19.450,0:17:20.828
this is a bad analogy,

0:17:20.828,0:17:23.542
but most Americans who don't live in Manhattan

0:17:23.542,0:17:25.086
get up in the morning and get in their cars

0:17:25.086,0:17:27.689
and turn on that ignition, and their cars work,

0:17:27.689,0:17:29.600
and they work incredibly well.

0:17:29.600,0:17:32.475
The modern automobile hardly ever breaks down.

0:17:32.475,0:17:35.358
So why is that? Why do cars work so well?

0:17:35.358,0:17:37.452
It's not because of the genius of Henry Ford

0:17:37.452,0:17:41.113
or Carl Benz or even Elon Musk.

0:17:41.113,0:17:42.905
It's because the modern automobile

0:17:42.905,0:17:47.939
is the product of more than 100 years of work

0:17:47.939,0:17:49.669
by hundreds and thousands

0:17:49.669,0:17:51.135
and tens of thousands of people.

0:17:51.135,0:17:53.226
The modern automobile is the product

0:17:53.226,0:17:55.615
of the collected work and wisdom and experience

0:17:55.615,0:17:58.212
of every man and woman who has ever worked

0:17:58.212,0:17:59.950
on a car,

0:17:59.950,0:18:02.635
and the reliability of the technology is the result

0:18:02.635,0:18:05.438
of that accumulated effort.

0:18:05.438,0:18:08.155
We benefit not just from the genius of Benz

0:18:08.155,0:18:09.551
and Ford and Musk

0:18:09.551,0:18:12.139
but from the collective intelligence and hard work

0:18:12.139,0:18:14.060
of all of the people who have worked

0:18:14.060,0:18:16.039
on the modern car.

0:18:16.039,0:18:18.180
And the same is true of science,

0:18:18.180,0:18:20.744
only science is even older.

0:18:20.744,0:18:23.528
Our basis for trust in science is actually the same

0:18:23.528,0:18:26.162
as our basis in trust in technology,

0:18:26.162,0:18:29.929
and the same as our basis for trust in anything,

0:18:29.929,0:18:32.447
namely, experience.

0:18:32.447,0:18:34.251
But it shouldn't be blind trust

0:18:34.251,0:18:37.301
any more than we would have blind trust in anything.

0:18:37.301,0:18:39.612
Our trust in science, like science itself,

0:18:39.612,0:18:41.655
should be based on evidence,

0:18:41.655,0:18:43.197
and that means that scientists

0:18:43.197,0:18:45.135
have to become better communicators.

0:18:45.135,0:18:47.982
They have to explain to us not just what they know

0:18:47.982,0:18:50.120
but how they know it,

0:18:50.120,0:18:53.610
and it means that we have[br]to become better listeners.

0:18:53.610,0:18:55.439
Thank you very much.

0:18:55.439,0:18:57.452
(Applause)