Why we should trust scientists

Every day we face issues like climate change

or the safety of vaccines

where we have to answer questions whose answers

rely heavily on scientific information.

Scientists tell us that the world is warming.

Scientists tell us that vaccines are safe.

But how do we know if they are right?

Why should be believe the science?

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

Public opinion polls consistently show

that significant proportions of the American people

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

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

and aren't persuaded by the safety of vaccines.

So why should we believe the science?

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

In fact, they would contract science with faith

and they would say belief is the domain, faith.

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

Indeed they would say religion is based on faith

or maybe the calculous of Pascal's wager.

Blaise Pascal was a 17th century mathematician

who tried to bring scientific reasoning to the question of

wether or not he should believe in God

and his wager went like this:

Well, if God doesn't exist but I decide to believe in him

nothing much is really lost.

Maybe a few hours on Sunday.

[Laughter]

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

then I'm in deep trouble.

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

Or as one of my college professors said,

"he clutched for the handmill of faith".

He made that leap of faith

leaving science and rationalism behind.

Now the fact is though, for most of us

most scientific claims are a leap of faith.

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

And indeed this is actually true for most scientists as well

outside of their own specialties.

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

wether a vaccine is safe.

Most chemists are not experts in evolutionary theory.

A physicist cannot tell you, despite the claims of some of them,

wether or not tobacco causes cancer.

So, if even scientists themselves have to make a leap of faith

outside their own fields,

then why do they accept the claims of other scientists?

Why do they believe each other's claims?

And should we believe those claims?

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

But not for the reason that most of us think.

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

believe in science is because of the scientific method.

We were taught that scientists follow a method

and that this method guarantees the truth of their claims.

The method that most of us were taught in school,

we can call it the text book method,

is the hypo-deductive method.

According to the standard model, the textbook model,

scientists develop hypotheses, they deduce the

consequences for those hypotheses,

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

Are those consequences true?

Can we observe them taking place in the natural world?

And if they are true, then the scientists say:

Great, we know the hypothesis is correct.

So there are many famous examples in the history

of science of scientists doing exactly this.

One of the most famous examples

comes from the work of Albert Einstein.

When Einstein developed the theory of general relativity

one of the consequences of his theory

was that space time wasn't just an empty void

but that it actually had a fabric.

And that that fabric was bent

in the presence of massive objects like the sun.

So if this theory were true then it meant that light

as it passed the sun

should actually be bent around it.

That was a pretty startling prediction

and it took a few years before scientists

were able to test it.

But they did test it in 1919

and low and behold it turned out to be true.

Starlight actually does bend as it travels around the sun.

This was a huge confirmation of the theory.

It was considered proof of the truth of this radical new idea

and it was written up in many newspapers around the globe.

Now sometimes this theory or this model

is referred to as the deductive-nomological model.

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

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

So nomological means having to do with laws.

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

ideally it is a law of nature.

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

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

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

in all times and all places

no matter what the circumstances are.

And all of you know at least one example of a famous law.

Einstein's famous equation, E=MC2,

which tells us what the relationship is

between energy and mass.

And that relationship is true no matter what.

It turns out though that there are
several problems with this model.

The main problem is that it's wrong.

It's just not true. [Laughter]

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

So the first reason is a logical reason,

it's the problem of the fallacy of affirming the consequent.

So that's another fancy academic way of saying

that false theories can make true predictions.

So just because the prediction comes true

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

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

This is a picture of the Ptolemaic universe

with the Earth at the center of the universe

and The Sun and the planets going around it.

The Ptolemaic model was believed

by many very smart people for many centuries.

Well why?

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

The Ptolemaic system enabled astronomers

to make accurate predictions of the motions of the planet.

In fact more accurate predictions at first

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

So that's one problem with the textbook model,

a second problem is a practical problem

and it's the problem of auxiliary hypotheses.

Auxiliary hypotheses are assumptions

that scientists are making,

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

So an important example of this comes from

comes from the Copernican model

which ultimately replaced the Ptolemaic system.

So when Nicolaus Copernicus said,

actually the Earth is not the center of the universe,

the sun is the center of the solar system,

the Earth moves around the sun.

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

we ought to be able to detect the motion

of the Earth around the sun.

And so this slide here illustrates a concept

known as stellar parallax.

And astronomers said, if the Earth is moving

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

Well I know I'm in Manhattan so you guys can't see the stars,

but imagine you're out in the country,
imagine you chose that rural life.

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

against the backdrop of distant stars.

If we now make the same observation six months later

when the Earth has moved to this position in June,

we look at that same star and we see it against a different backdrop.

That difference, that angular difference, is the stellar parallax.

So this is the prediction that the Copernican model makes,

astronomers looked for the stellar parallax

and they found nothing, nothing at all.

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

So what happened?

Well in hindsight we can say that astronomers were making

two auxiliary hypotheses, both of which

we would now say were incorrect.

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

Astronomers were assuming that the Earth's orbit was large

relative to the stars.

Today we would draw the picture more like this,

this comes from NASA,

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

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

The stellar parallax therefore,

is very small and actually very hard to detect.

And that leads to the second reason

why the prediction didn't work,

because scientists were also assuming

that the telescopes they had were sensitive enough

to detect the parallax.

And that turned out not to be true.

It wasn't until the 19th century that scientists were able to detect

the stellar parallax.

So, there's a third problem as well.

The third problem is simply a factual problem

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

A lot of science isn't deductive at all, it's actually inductive.

And by that we mean that scientists don't necessarily

start with theories and hypotheses, often they just

start with observations of stuff going on in the world.

And the most famous example of that is one of the most

famous scientists who ever lived, Charles Darwin.

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

he didn't have a hypothesis, he didn't have a theory.

He just knew that he wanted to have a career as a scientist

and he started to collect data.

Mainly he knew that he hated medicine

because the sight of blood made him sick so

he had to have an alternative career path.

So he started collecting data.

And he collected many things including his famous finches.

When he collected these finches he through them in a bag

and he had no idea what they meant.

Many years later back in London,

Darwin looked at his data again and began to develop

an explanation

and that explanation was the theory of natural selection.

Besides inductive science,

scientists also often participate in modeling.