The scientific method is crap | Teman Cooke | TEDxLancaster

Teman Cooke hold a Ph.D. in theoretical physics but has no love for the scientific method. He explains an interesting alternative that will challenge your thinking.

This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at http://ted.com/tedx

The scientific method sucks.

(Laughter)

Now, by that I don't mean
that science sucks.

As a physicist, I believe that science
has had countless benefits for humanity.

But when I was in eigth grade,

I learned about this thing
called the scientific method.

And since then, I have done science,
I have worked with other scientists

and I've taught science

to college students,

to K-12 teachers,

and to seventh and eighth graders -
middle schoolers.

And from these experiences,
I've come to the conclusion

that the scientific method ... sucks.

If it's been a while for you,

as it has been for me,
since middle school,

let me run through it real quick for you.

First of all, Step 1: Identify a problem.

Step 2: Do some research.

Step 3: Form a hypothesis.

Step 4: Do an experiment with some
independent and dependent variables

to test your hypothesis.

Step 5: Analyze data.

Step 6: Draw a conclusion.

It sounds good, right?

It certainly matches
what we see on TV and in movies,

and what we see on the news.

Unfortunately, it completely misrepresents

what scientists do
and what science is all about.

And this manifests in four main ways:

First of all, it's incredibly linear.

We start with a problem statement,
and we end with a conclusion.

This implies that science
is something that's once and done,

fixed for all time.

Secondly, it's not very intuitive.

How do I choose a problem?

What do I do with
my conclusion when I'm done?

If I have no idea what should
or even could happen,

how do I come up with a hypothesis?

This makes the process intimidating

and dangerous.

Three, there's a focus on conclusion -

reaching the conclusion,
on getting a fact.

Well, what happens
when the information changes?

What happens when facts change?

How does this process capture that?

And finally, the focus on experimentation.

Now, don't get me wrong,
I'm a big fan of teaching students

to control for whatever
random variables they can,

but there's been a lot
of really good science that's been done

without being able to control
for, well, anything.

For a moment, I'd like for you to imagine

what budget it would take
to create a laboratory here on Earth

to study the interior of Jupiter.

Or to form a star from scratch.

Or to study a galaxy's development.

Do you want your tax dollars
to go towards that?

Now, you may be thinking,
well, it's probably not that bad.

I mean, we've trained generations
of scientists using the scientific method,

myself included,

surely, I'm exaggerating.

Well, let me walk through
a few statistics with you.

65 percent of Americans
have little to no idea

what scientists do on a day-to-day basis.

(Laughter)

50 percent of them, however,
have considered it,

whatever it is, dangerous.

(Laughter)

32 percent of middle schoolers,
of eighth graders,

score at or above proficiency
in science, in 2011.

The good news is,
that's up from 30 percent in 2009.

The bad new is, that implies 68 percent,
two thirds, middle schoolers,

score below proficiency.

30 percent of elementary school teachers
feel well prepared to teach science.

Now that's compared to 52 percent

who feel well prepared
to teach social studies,

66 percent who feel
well prepared to teach mathematics,

and 77 percent who feel well prepared
to teach reading and language arts.

But here's my favorite statistic of all,
the one I find most telling.

Of 2,000 parents surveyed in the UK,

50 percent said that they feared

answering their children's
questions about science -

questions like, why is the sky blue?

And why is the moon out
during the daytime?

20 percent, one in five,
said that in response to such questions,

they said, "No one knows"
or made somethig up.

(Laughter)

This concerns me.

As a culture, as a civilization,
we fear science.

Why?

Well, I believe there are
three main sources of that.

First of all, we're obsessed
with right answers,

we're obsessed with conclusions.

And as we go further and further,
we learn more and more stuff,

we can't keep track of it all.

In addition, the facts,
those conclusions, change.

Let me give you an example.

If you're like me,
when you were growing up,

there were nine planets
in the solar system.

In 2006,

one of these things was eliminated.

Which brings me to my third point:

Why?!

(Laughter)

We don't understand
how do these decisions get made.

We don't understand
the thought process behind it.

Now, all of these problems possibly don't
lie at the feet of the scientific method,

but it's not helping.

There is, however, a better way.

Let me introduce you
to the cycle of scientific thinking.

This starts with interesting observations.

What counts as interesting?

Well, if you find yourself
asking the question:

What happened there?

Why did that occur?

What's going on?

It's probably interesting.

In the face of such questions,
the human brain does an amazing thing:

It tries to come up with an answer,
a story, an explanation

of what's going on.

Now, a lot of people
are perfectly happy to have an answer.

But scientists - and this is what makes
scientists different from other people -

scientists want to know
if their answer is right.

And the way they do that is by saying,

"Well, if my explanation
is true, is correct,

then I should also see this ..."
They make a prediction.

And once you have a prediction,
the only thing left to do

is to go make an observation,
is to see if you were right.

And if you are, yay!

But if you're not, if you're truly lucky,
and you got it wrong,

then that's going
to bring up more questions -

questions that require more explanation.

Which leads to new predictions.

And so on, and so on, and so on.

Now, why is this better?

Well, first of all, it actually
represents what scientists do.

In fact, post-graduate
education in science

is all about teaching people
how to take interesting observations,

ask pertinent questions,

and then develop explanations
that lead to observable predictions.

This is science.

But secondly, and more importantly,
it's much more intuitive

and much more engaging.

The power is in your hands.

Once you have an interesting question,
do you want to go to the library

and read up on other people's answers?

Or do you want to skip all that
and come up with an answer of your own,

and see if you can make
a prediction and test it?

It's up to you.

That makes it much less intimidating.

From this, as well,
it becomes much more obvious

how examples, how explanations,
change over time.

In fact, there are only
three possible things

that can happen to a scientific model:

It makes the right predictions,

in which case it becomes
stronger over time;

it makes a few wrong predictions,

in which case it is modified over time;

or it makes completely wrong predictions,

in which case it will be
abandoned over time.

The last great thing about this model

is that it also illuminates something
that's very dear to my heart:

the idea that any explanation
must be able to be proven false.

And to explain this, I want to start with:

What would it take for me to show

that my explanation of a phenomenon
is True, with a capital 'T'?

Well if it's true,
then every prediction it makes

should match the observations.

Well how do I check that?

I have to check "every" observation.

That's not "every observation
that I can make with my current budget."

That's not "every observation
that I can make here

in this amount of time that I have."

It's "every" observation.

Everywhere. Everywhen.

It's not possible.

In order to prove
an explanation false, however,

all I have to do is find out
that it makes the wrong predictions,

and then make sure
that I didn't make a mistake.

The way I think of this is to say:

If you give me a model that consistently
predicts the wrong thing,

I can say with certainty,
your model is wrong.

If you give me a model that consistently
predicts the right thing,

I can say with certainty
that your model is not wrong ...

yet.

Let me give you an example.

In 1781, we found the planet Uranus.

But it did this really weird thing.

At certain points in its orbit,
it was further along than we expected

based upon our models,
our understanding of gravity.

And at other points in its orbits,
it hadn't traveled far enough.

It was almost as if it was traveling
too fast at some points

and not fast enough at other points.

Astronomers looked at this, and they said,

"You know, it looks a lot
like something is pulling it -

pulling it a little bit faster
or a little bit slower

depending on where it is in its orbit.

Maybe there's a planet out there.

Maybe there's something
interacting with it gravitationally."

And so they did the calculations,
they found out where the planet should be,

and they pointed their telescopes
in the sky at that location.

The planet they found
we call Neptune, today.

Now, this was awesome
to be able to do this,

and there were still discrepancies
in Uranus's orbit.

So they did calculations,

they said maybe there's
another planet out there, planet X.

They did the calculations,

they figured out
where that planet should be,

and they pointed their telescopes
into the sky at that point,

and they looked and they found ...

nothing.

And this was a problem.

And they said, "Okay,"
but they continued to look.

And eventually they saw something.

And it wasn't where they expected,

and it wasn't really
the size they expected,

but they said, "We found something,
and it's a planet,

and we're going to call that thing Pluto."

Fast forward 60 years.

Astronomers continued looking,
continued taking observations.

And another one popped up.

Same size, same composition,
same location.

And then another one,

and another one,

and another one,

and another one.

And astronomers said, "Uh oh.

This is not looking so much
like the other planets,

this is looking like the asteroid belt -

a collection of objects
that all share the same orbit

but aren't really planets,
not what we think of as planets."

And as the evidence,
as the observations continued to build,

astronomers ended up having to abandon

this explanation of Pluto
as being a planet -

it didn't fit.

In the same way, we need to abandon
the scientific model.

It doesn't fit.

Instead, embrace
the cycle of scientific thinking.

You don't have to be
an expert to do science.

You don't have to know everything

to answer your kid's
questions about science.

Even if the answer is: I don't know.

What do you think?

Observe.

Explain.

Predict.

That's enough; it's good enough.

Together, as parents,
as educators, and as scientists,

we can prepare our kids, our students,
our schools, and our country

for the challenges
of the 21st century and beyond,

if we can learn to think differently
about science over time.

Thank you very much.

(Applause)