0:00:00.930,0:00:04.058
Every day we face issues like climate change

0:00:04.058,0:00:05.488
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 contrast 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 calculus of Pascal's wager.

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Blaise Pascal was a 17th-century mathematician

0:01:06.560,0:01:09.370
who tried to bring scientific[br]reasoning to the question of

0:01:09.370,0:01:11.242
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 handrail 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 textbook 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 of 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

0:04:03.428,0:04:04.740
of this radical new idea,

0:04:04.740,0:04:06.592
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

0:04:11.480,0:04:14.914
is referred to as the deductive-nomological model,

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mainly because academics like [br]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 of 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

0:04:51.168,0:04:53.361
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 [br]are several problems with this model.

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The main problem is that it's wrong.

0:05:04.645,0:05:08.147
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.

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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,

0:06:27.177,0:06:29.827
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

0:06:42.633,0:06:44.441
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 --

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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.

0:07:03.240,0:07:06.194
If we now make the same observation six months later

0:07:06.194,0:07:10.006
when the Earth has moved to this position in June,

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we look at that same star and we [br]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 a prediction that the Copernican model makes.

0:07:21.150,0:07:23.711
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?

0:07:34.047,0:07:36.730
Well, in hindsight we can say [br]that astronomers were making

0:07:36.730,0:07:39.277
two auxiliary hypotheses, both of which

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we would now say were incorrect.

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The first was an assumption [br]about the size of the Earth's orbit.

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Astronomers were assuming [br]that the Earth's orbit was large

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relative to the distance to the stars.

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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.

0:08:00.174,0:08:01.713
The stellar parallax therefore,

0:08:01.713,0:08:05.297
is very small and actually very hard to detect.

0:08:05.297,0:08:07.271
And that leads to the second reason

0:08:07.271,0:08:09.130
why the prediction didn't work,

0:08:09.130,0:08:11.045
because scientists were also assuming

0:08:11.045,0:08:14.055
that the telescopes they had were sensitive enough

0:08:14.055,0:08:15.955
to detect the parallax.

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And that turned out not to be true.

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It wasn't until the 19th century

0:08:20.506,0:08:22.190
that scientists were able to detect

0:08:22.190,0:08:23.726
the stellar parallax.

0:08:23.726,0:08:26.372
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,

0:08:40.754,0:08:42.623
often they just start with observations

0:08:42.623,0:08:45.032
of stuff going on in the world.

0:08:45.032,0:08:47.602
And the most famous example[br]of that is one of the most

0:08:47.602,0:08:50.667
famous scientists who ever lived, Charles Darwin.

0:08:50.667,0:08:53.829
When Darwin went out as a young [br]man on the voyage of the Beagle,

0:08:53.829,0:08:57.441
he didn't have a hypothesis, he didn't have a theory.

0:08:57.441,0:09:00.507
He just knew that he wanted[br]to have a career as a scientist

0:09:00.507,0:09:02.519
and he started to collect data.

0:09:02.519,0:09:05.249
Mainly he knew that he hated medicine

0:09:05.249,0:09:07.067
because the sight of blood made him sick so

0:09:07.067,0:09:09.335
he had to have an alternative career path.

0:09:09.335,0:09:11.469
So he started collecting data.

0:09:11.469,0:09:14.635
And he collected many things, [br]including his famous finches.

0:09:14.635,0:09:16.845
When he collected these finches,[br]he threw them in a bag

0:09:16.845,0:09:19.185
and he had no idea what they meant.

0:09:19.185,0:09:21.472
Many years later back in London,

0:09:21.472,0:09:23.705
Darwin looked at his data again and began

0:09:23.705,0:09:26.153
to develop an explanation,

0:09:26.153,0:09:29.451
and that explanation was the[br]theory of natural selection.

0:09:29.451,0:09:31.510
Besides inductive science,

0:09:31.510,0:09:34.446
scientists also often participate in modeling.

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One of the things scientists want to do in life

0:09:36.782,0:09:39.050
is to explain the causes of things.

0:09:39.050,0:09:40.568
And how do we do that?

0:09:40.568,0:09:42.820
Well, one way you can do it is to build a model

0:09:42.820,0:09:44.562
that tests an idea.

0:09:44.562,0:09:46.493
So this is a picture of Henry Cadell,

0:09:46.493,0:09:49.359
who was a Scottish geologist in the 19th century.

0:09:49.359,0:09:50.792
You can tell he's Scottish because he's wearing

0:09:50.792,0:09:53.180
a deerstalker cap and Wellington boots.

0:09:53.180,0:09:55.334
(Laughter)

0:09:55.334,0:09:56.900
And Cadell wanted to answer the question,

0:09:56.900,0:09:58.668
how are mountains formed?

0:09:58.668,0:10:00.184
And one of the things he had observed

0:10:00.184,0:10:02.758
is that if you look at mountains[br]like the Appalachians,

0:10:02.758,0:10:04.391
you often find that the rocks in them

0:10:04.391,0:10:05.860
are folded,

0:10:05.860,0:10:07.506
and they're folded in a particular way,

0:10:07.506,0:10:08.950
which suggested to him

0:10:08.950,0:10:11.899
that they were actually being[br]compressed from the side.

0:10:11.899,0:10:13.987
And this idea would later play a major role

0:10:13.987,0:10:16.410
in discussions of continental drift.

0:10:16.410,0:10:18.916
So he built this model, this crazy contraption

0:10:18.916,0:10:21.068
with levers and wood, and here's his wheelbarrow,

0:10:21.068,0:10:23.510
buckets, a big sledgehammer.

0:10:23.510,0:10:25.408
I don't know why he's got the Wellington boots.

0:10:25.408,0:10:26.985
Maybe it's going to rain.

0:10:26.985,0:10:30.070
And he created this physical model in order

0:10:30.070,0:10:34.035
to demonstrate that you could, in fact, create

0:10:34.035,0:10:36.709
patterns in rocks, or at least, in this case, in mud,

0:10:36.709,0:10:38.935
that looked a lot like mountains

0:10:38.935,0:10:40.777
if you compressed them from the side.

0:10:40.777,0:10:44.405
So it was an argument about[br]the cause of mountains.

0:10:44.405,0:10:47.453
Nowadays, most scientists prefer to work inside,

0:10:47.453,0:10:49.880
so they don't build physical models so much

0:10:49.880,0:10:52.241
as to make computer simulations.

0:10:52.241,0:10:55.080
But a computer simulation is a kind of a model.

0:10:55.080,0:10:56.943
It's a model that's made with mathematics,

0:10:56.943,0:11:00.176
and like the physical models of the 19th century,

0:11:00.176,0:11:03.954
it's very important for thinking about causes.

0:11:03.954,0:11:06.569
So one of the big questions[br]to do with climate change,

0:11:06.569,0:11:08.372
we have tremendous amounts of evidence

0:11:08.372,0:11:10.252
that the Earth is warming up.

0:11:10.252,0:11:12.716
This slide here, the black line shows

0:11:12.716,0:11:14.836
the measurements that scientists have taken

0:11:14.836,0:11:16.799
for the last 150 years

0:11:16.799,0:11:18.209
showing that the Earth's temperature

0:11:18.209,0:11:19.843
has steadily increased,

0:11:19.843,0:11:22.689
and you can see in particular[br]that in the last 50 years

0:11:22.689,0:11:24.453
there's been this dramatic increase

0:11:24.453,0:11:26.793
of nearly one degree centigrade,

0:11:26.793,0:11:29.168
or almost two degrees Fahrenheit.

0:11:29.168,0:11:31.605
So what, though, is driving that change?

0:11:31.605,0:11:33.940
How can we know what's causing

0:11:33.940,0:11:35.456
the observed warming?

0:11:35.456,0:11:37.170
Well, scientists can model it

0:11:37.170,0:11:39.538
using a computer simulation.

0:11:39.538,0:11:42.330
So this diagram illustrates a computer simulation

0:11:42.330,0:11:44.451
that has looked at all the different factors

0:11:44.451,0:11:47.056
that we know can influence the Earth's climate,

0:11:47.056,0:11:49.808
so sulfate particles from air pollution,

0:11:49.808,0:11:52.778
volcanic dust from volcanic eruptions,

0:11:52.778,0:11:55.012
changes in solar radiation,

0:11:55.012,0:11:57.390
and, of course, greenhouse gases.

0:11:57.390,0:11:59.208
And they asked the question,

0:11:59.208,0:12:02.904
what set of variables put into a model

0:12:02.904,0:12:05.880
will reproduce what we actually see in real life?

0:12:05.880,0:12:07.900
So here is the real life in black.

0:12:07.900,0:12:10.180
Here's the model in this light gray,

0:12:10.180,0:12:11.740
and the answer is

0:12:11.740,0:12:16.127
a model that includes, it's the answer E on that SAT,

0:12:16.127,0:12:18.268
all of the above.

0:12:18.268,0:12:19.774
The only way you can reproduce

0:12:19.774,0:12:21.602
the observed temperature measurements

0:12:21.602,0:12:23.580
is with all of these things put together,

0:12:23.580,0:12:25.719
including greenhouse gases,

0:12:25.719,0:12:28.270
and in particular you can see that the increase

0:12:28.270,0:12:30.154
in greenhouse gases tracks

0:12:30.154,0:12:32.360
this very dramatic increase in temperature

0:12:32.360,0:12:33.840
over the last 50 years.

0:12:33.840,0:12:36.274
And so this is why climate scientists say

0:12:36.274,0:12:39.382
it's not just that we know that[br]climate change is happening,

0:12:39.382,0:12:42.150
we know that greenhouse gases are a major part

0:12:42.150,0:12:44.880
of the reason why.

0:12:44.880,0:12:47.268
So now because there all these different things

0:12:47.268,0:12:48.757
that scientists do,

0:12:48.757,0:12:52.243
the philosopher Paul Feyerabend famously said,

0:12:52.243,0:12:53.869
"The only principle in science

0:12:53.869,0:12:57.848
that doesn't inhibit progress is: anything goes."

0:12:57.848,0:13:00.464
Now this quotation has often[br]been taken out of context,

0:13:00.464,0:13:02.582
because Feyerabend was not actually saying

0:13:02.582,0:13:04.532
that in science anything goes.

0:13:04.532,0:13:05.876
What he was saying was,

0:13:05.876,0:13:07.900
actually the full quotation is,

0:13:07.900,0:13:09.990
"If you press me to say

0:13:09.990,0:13:11.636
what is the method of science,

0:13:11.636,0:13:15.265
I would have to say: anything goes."

0:13:15.265,0:13:16.343
What he was trying to say

0:13:16.343,0:13:18.910
is that scientists do a lot of different things.

0:13:18.910,0:13:21.218
Scientists are creative.

0:13:21.218,0:13:23.328
But then this pushes the question back:

0:13:23.328,0:13:26.799
If scientists don't use a single method,

0:13:26.799,0:13:28.698
then how do they decide

0:13:28.698,0:13:30.156
what's right and what's wrong?

0:13:30.156,0:13:32.050
And who judges?

0:13:32.050,0:13:34.130
And the answer is, scientists judge,

0:13:34.130,0:13:37.013
and they judge by judging evidence.

0:13:37.013,0:13:40.422
Scientists collect evidence in many different ways,

0:13:40.422,0:13:42.044
but however they collect it,

0:13:42.044,0:13:44.621
they have to subject it to scrutiny.

0:13:44.621,0:13:47.181
And this led the sociologist Robert Merton

0:13:47.181,0:13:49.361
to focus on this question of how scientists

0:13:49.361,0:13:51.040
scrutinize data and evidence,

0:13:51.040,0:13:53.848
and he said they do it in a way he called

0:13:53.848,0:13:55.767
"organized skepticism."

0:13:55.767,0:13:57.651
And by that he meant it's organized

0:13:57.651,0:13:59.129
because they do it collectively,

0:13:59.129,0:14:00.758
they do it as a group,

0:14:00.758,0:14:03.574
and skepticism, because they do it from a position

0:14:03.574,0:14:05.028
of distrust.

0:14:05.028,0:14:06.990
That is to say, the burden of proof

0:14:06.990,0:14:09.471
is on the person with a novel claim.

0:14:09.471,0:14:12.614
And in this sense, science[br]is intrinsically conservative.

0:14:12.614,0:14:15.186
It's quite hard to persuade the scientific community

0:14:15.186,0:14:18.897
to say, "Yes, we know something, this is true."

0:14:18.897,0:14:21.393
So despite the popularity of the concept

0:14:21.393,0:14:22.990
of paradigm shifts,

0:14:22.990,0:14:24.274
what we find is that actually,

0:14:24.274,0:14:27.059
really major changes in scientific thinking

0:14:27.059,0:14:30.779
are relatively rare in the history of science.

0:14:30.779,0:14:34.342
So finally that brings us to one more idea:

0:14:34.342,0:14:38.050
If scientists judge evidence collectively,

0:14:38.050,0:14:40.612
this has led historians to focus on the question

0:14:40.612,0:14:42.031
of consensus,

0:14:42.031,0:14:43.926
and to say that at the end of the day,

0:14:43.926,0:14:45.860
what science is,

0:14:45.860,0:14:47.530
what scientific knowledge is,

0:14:47.530,0:14:50.909
is the consensus of the scientific experts

0:14:50.909,0:14:53.063
who through this process of organized scrutiny,

0:14:53.063,0:14:55.368
collective scrutiny,

0:14:55.368,0:14:56.610
have judged the evidence

0:14:56.610,0:14:59.407
and come to a conclusion about it,

0:14:59.407,0:15:01.884
either yea or nay.

0:15:01.884,0:15:03.608
So we can think of scientific knowledge

0:15:03.608,0:15:05.660
as a consensus of experts.

0:15:05.660,0:15:07.432
We can also think of science as being

0:15:07.432,0:15:09.010
a kind of a jury,

0:15:09.010,0:15:11.524
except it's a very special kind of jury.

0:15:11.524,0:15:13.628
It's not a jury of your peers,

0:15:13.628,0:15:15.524
it's a jury of geeks.

0:15:15.524,0:15:19.158
It's a jury of men and women with Ph.D.s,

0:15:19.158,0:15:21.600
and unlike a conventional jury,

0:15:21.600,0:15:23.290
which has only two choices,

0:15:23.290,0:15:25.975
guilty or not guilty,

0:15:25.975,0:15:29.376
the scientific jury actually has a number of choices.

0:15:29.376,0:15:32.160
Scientists can say yes, something's true.

0:15:32.160,0:15:34.740
Scientists can say no, it's false.

0:15:34.740,0:15:37.280
Or, they can say, well it might be true

0:15:37.280,0:15:40.324
but we need to work more[br]and collect more evidence.

0:15:40.324,0:15:41.940
Or, they can say it might be true,

0:15:41.940,0:15:43.640
but we don't know how to answer the question

0:15:43.640,0:15:44.950
and we're going to put it aside

0:15:44.950,0:15:47.873
and maybe we'll come back to it later.

0:15:47.873,0:15:51.875
That's what scientists call "intractable."

0:15:51.875,0:15:54.481
But this leads us to one final problem:

0:15:54.481,0:15:57.419
If science is what scientists say it is,

0:15:57.419,0:15:59.960
then isn't that just an appeal to authority?

0:15:59.960,0:16:01.022
And weren't we all taught in school

0:16:01.022,0:16:04.249
that the appeal to authority is a logical fallacy?

0:16:04.249,0:16:07.281
Well, here's the paradox of modern science,

0:16:07.281,0:16:09.553
the paradox of the conclusion I think historians

0:16:09.553,0:16:12.154
and philosophers and sociologists have come to,

0:16:12.154,0:16:15.655
that actually science is the appeal to authority,

0:16:15.655,0:16:19.431
but it's not the authority of the individual,

0:16:19.431,0:16:21.830
no matter how smart that individual is,

0:16:21.830,0:16:25.695
like Plato or Socrates or Einstein.

0:16:25.695,0:16:28.809
It's the authority of the collective community.

0:16:28.809,0:16:31.795
You can think of it is a kind of wisdom of the crowd,

0:16:31.795,0:16:35.921
but a very special kind of crowd.

0:16:35.921,0:16:37.811
Science does appeal to authority,

0:16:37.811,0:16:39.861
but it's not based on any individual,

0:16:39.861,0:16:42.447
no matter how smart that individual may be.

0:16:42.447,0:16:44.198
It's based on the collective wisdom,

0:16:44.198,0:16:46.840
the collective knowledge, the collective work,

0:16:46.840,0:16:48.738
of all of the scientists who have worked

0:16:48.738,0:16:51.455
on a particular problem.

0:16:51.455,0:16:54.251
Scientists have a kind of culture of collective distrust,

0:16:54.251,0:16:56.451
this "show me" culture,

0:16:56.451,0:16:58.401
illustrated by this nice woman here

0:16:58.401,0:17:01.483
showing her colleagues her evidence.

0:17:01.483,0:17:03.340
Of course, these people don't[br]really look like scientists,

0:17:03.340,0:17:05.326
because they're much too happy.

0:17:05.326,0:17:09.338
(Laughter)

0:17:09.338,0:17:13.660
Okay, so that brings me to my final point.

0:17:13.660,0:17:16.308
Most of us get up in the morning.

0:17:16.308,0:17:17.718
Most of us trust our cars.

0:17:17.718,0:17:19.260
Well, see, now I'm thinking, I'm in Manhattan,

0:17:19.260,0:17:20.558
this is a bad analogy,

0:17:20.558,0:17:23.382
but most Americans who don't live in Manhattan

0:17:23.382,0:17:25.120
get up in the morning and get in their cars

0:17:25.120,0:17:27.649
and turn on that ignition, and their cars work,

0:17:27.649,0:17:29.650
and they work incredibly well.

0:17:29.650,0:17:32.365
The modern automobile hardly ever breaks down.

0:17:32.365,0:17:35.148
So why is that? Why do cars work so well?

0:17:35.148,0:17:37.652
It's not because of the genius of Henry Ford

0:17:37.652,0:17:40.743
or Karl Benz or even Elon Musk.

0:17:40.743,0:17:42.885
It's because the modern automobile

0:17:42.885,0:17:47.919
is the product of more than 100 years of work

0:17:47.919,0:17:49.509
by hundreds and thousands

0:17:49.509,0:17:50.845
and tens of thousands of people.

0:17:50.845,0:17:52.956
The modern automobile is the product

0:17:52.956,0:17:55.745
of the collected work and wisdom and experience

0:17:55.745,0:17:58.092
of every man and woman who has ever worked

0:17:58.092,0:17:59.700
on a car,

0:17:59.700,0:18:02.615
and the reliability of the technology is the result

0:18:02.615,0:18:05.298
of that accumulated effort.

0:18:05.298,0:18:08.155
We benefit not just from the genius of Benz

0:18:08.155,0:18:09.221
and Ford and Musk

0:18:09.221,0:18:11.989
but from the collective intelligence and hard work

0:18:11.989,0:18:14.240
of all of the people who have worked

0:18:14.240,0:18:15.910
on the modern car.

0:18:15.910,0:18:17.960
And the same is true of science,

0:18:17.960,0:18:20.804
only science is even older.

0:18:20.804,0:18:23.378
Our basis for trust in science is actually the same

0:18:23.378,0:18:26.052
as our basis in trust in technology,

0:18:26.052,0:18:30.039
and the same as our basis for trust in anything,

0:18:30.039,0:18:32.317
namely, experience.

0:18:32.317,0:18:34.161
But it shouldn't be blind trust

0:18:34.161,0:18:36.921
any more than we would have blind trust in anything.

0:18:36.921,0:18:39.762
Our trust in science, like science itself,

0:18:39.762,0:18:41.675
should be based on evidence,

0:18:41.675,0:18:43.177
and that means that scientists

0:18:43.177,0:18:45.225
have to become better communicators.

0:18:45.225,0:18:48.112
They have to explain to us not just what they know

0:18:48.112,0:18:49.840
but how they know it,

0:18:49.840,0:18:53.730
and it means that we have[br]to become better listeners.

0:18:53.730,0:18:55.149
Thank you very much.

0:18:55.149,0:18:57.452
(Applause)