- Hi there, welcome to Up and Atom. I'm Jade.
"A good scientist achieves the point of view
of no-one in particular."
These were the words of the astronomer Arthur Eddington,
whose physics experiments helped verify
Einstein's general theory of relativity.
We value science because of its objectivity,
its ability to remain unbiased and impartial.
A good scientist doesn't let their own personal fears,
hopes, or expectations interfere with their work.
This quality of objectivity
is the reason science has a special authority over society.
We stop smoking because science says it's bad for us.
We believe we've detected the Higgs boson,
even if we don't understand
the academic papers written about it.
And we try to cut our carbon emissions
because science says it will help stop global warming.
But if science really is objective, how do you explain this?
In March 2020, scientists in Europe
didn't know much about COVID-19, nor did governments,
yet they had to make a choice
between two possible strategies for handling the pandemic.
Choice one was suppression.
The goal of this strategy
was to minimize the spread of COVID-19
across all communities,
from the most vulnerable to the least vulnerable.
The idea was to use population-based interventions
like lockdowns, face masks, and social distancing.
Choice two was mitigation.
The goal of this strategy
was to avoid overwhelming hospitals.
Public health interventions were limited
to the most vulnerable, like the elderly,
while transmission was allowed
among the least vulnerable, like young adults.
In the beginning of the pandemic,
many countries like the UK
opted for the mitigation strategy,
with Boris Johnson warning Brits
to prepare to lose loved ones before their time.
But then on March 16th, 2020, the COVID-19 Response Team
at the Imperial College London published a shocking report.
The report included a model
stating that a suppression strategy
would have saved hundreds of thousands of lives.
The first author was Neil Ferguson,
a professor of mathematical biology at the Imperial College,
leader of the Imperial College COVID-19 Response Team,
and at the time a member
of the British Scientific Advisory Group for Emergencies,
aka SAGE.
The paper caused a sudden U-turn
in the UK government's response to COVID-19,
and influenced many other countries,
such as the US, France, and Germany to follow suit.
But there was one noticeable exception: Sweden.
The Swedish scientific community
harshly criticized the Imperial College's model.
One of the main critics of the model was Johan Giesecke,
Professor Emeritus at the Karolinska Institute of Stockholm,
epidemiologist at the World Health Organization,
and back then current advisor
to the Public Health Agency of Sweden.
Giesecke claimed that the Imperial College's
conclusion was wrong,
and that suppression was not the best strategy.
Sweden stuck to mitigation.
If science really is objective,
how is it that two super well-known, well-respected
and multi-award winning scientists
can end up disagreeing with each other?
They were presented with the same evidence
and were both following the scientific method.
Well, let's see how a scientific disagreement even arises.
In the beginning of the pandemic,
scientists knew very little about COVID,
and the evidence available to them
was mostly the hard data coming from China and Italy,
data such as COVID's fatality rate
and the proportion between infected and recovered people.
Maybe because they were scarce,
maybe because they were not very reliable,
these data seemed suitable to more than one interpretation.
This isn't a rare phenomenon, quite the opposite.
It happens so often that philosophers of science
have coined an expression
especially for it: underdetermination.
Underdetermination refers to the problem
that often more than one theory
is compatible with the evidence.
Suppose we're two scientists
who have just performed a study
and collected some data points.
We agree that all the data points we have are genuine data
and not outliers or artifacts.
The X and Y axes represent
the two factors we're interested in.
I think that these points support the hypothesis
that the relation between X and Y is a linear one,
whereas you think that the relationship
between X and Y is more complicated.
There's a mathematical theorem
called the interpolation theorem,
which proves that there are not only many,
but infinitely many curves
that can fit a set of data points.
The three points underdetermine the shape of the curve,
and therefore the scientific hypothesis that fits them.
Now, you might be thinking,
"But this is just because we have only three data points.
Scientists collect way more data than that.
Your analogy is flawed, Jade," and you're right.
Usually the data sets of scientists
are way larger than three points,
but this doesn't completely solve the problem.
Assume we add a fourth or fifth point
and these new points happen to all fit the straight line.
Maybe one or even both of these curves
will be shown to be incorrect.
The problem is that there will still be an infinite group
of other more intricate curves
that are compatible with the extended set of data points.
So even if we collect more data,
the evidence is still suitable
to more than one reasonable interpretation.
The point of all of this is,
sometimes the evidence can support two hypotheses
that are incompatible with each other.
So when this happens,
how do scientists choose between them?
According to the physicist turned philosopher Thomas Kuhn,
scientists choose one hypothesis over another
according to how well it fares
with respect to a list of scientific criteria.
These criteria are the characteristics
of a good scientific theory.
Some of them are accuracy, broad scope, and simplicity.
A good scientific theory
needs to agree with the experiments and observations.
A theory that predicts phenomena
that never occur in real life is completely useless.
The theory should also extend far beyond
the particular observations, laws, or sub-theories
it was initially designed to explain.
We want to make connections with other topics in the field,
and ideally with other disciplines as well.
And finally, the theory needs
to bring order in our knowledge
and unify phenomena
that were previously isolated and confused.
These are just a few criteria
for choosing the best scientific theory.
So if all we need to do
is choose the theory that best fits the criteria,
why do we end up with wildly different,
even conflicting theories?
Well, different theories fare differently
with respect to these criteria.
For example, hypothesis A might be easier to work with
than hypothesis B,
but hypothesis B might make more accurate predictions.
Although these criteria
are universally shared in the scientific community,
scientists can weigh them differently.
I might care more about simplicity, for example,
while you think accuracy is more important.
As a result, scientists can come to disagree
about which theory is better
or over which hypothesis to choose.
History is full of disagreements stemming from scientists
assigning different weights to different criteria.
About 100 years ago, there was a huge disagreement
between chemists and physicists
over whether or not atoms existed.
The idea that all matter is made up of tiny atoms
had been around since the fourth century BC,
when it was first put forth by Democritus,
the Laughing Philosopher,
but it made it as a scientific theory only in 1808
with the English chemist John Dalton.
Dalton didn't provide any direct evidence
for the existence of atoms,
but instead he showed how the idea of them
shed light on some otherwise puzzling physical phenomena.
For example, it was known that the atmosphere
was composed of at least two different gases:
oxygen and nitrogen.
Because oxygen is heavier than nitrogen,
it should form a distinct layer at the bottom
and the nitrogen gas should be at the top,
but this isn't what we see.
Instead, we see the atmosphere as a big, uniform mass.
Dalton argued that the existence
of indivisible microscopic particles
that rearrange themselves when oxygen and nitrogen react
was a simple explanation that resolved the issue.
Less than a century later,
the entire field of chemistry relied on atoms
to make sense of their field,
considering them a fact of nature.
But physicists remained skeptical.
They believed that for something
to count as a scientific theory,
it needed experimental evidence.
They wouldn't accept the theory of atoms
without further proof.
They claimed that atoms were pictorial representations
that one should not take literally.
Kuhn's theory about differing criteria
sheds light on this disagreement
between chemistry and physics.
In the 19th century,
most of the progress in chemistry
was based on atomic theory.
Drop the assumption that atoms exist
and it becomes very hard, almost impossible,
to make sense of a chemical reaction.
Unsurprisingly, the fruitfulness of the theory
was very much valued by chemists.
On the other hand, 19th century physicists
cared more about direct evidence.
Chemists had not seen atoms,
nor were they in a position to measure them directly.
Without that, physicists were still unsure
about whether atoms existed.
Lack of direct evidence trumped fruitfulness.
So what do we do
when we have these kinds of disagreements in science?
We can't really have a to-each-their-own attitude
about what matter is made of,
or what to do when thousands of lives are at stake.
That would completely invalidate
the authority and value of science.
In the ideal case, we keep exploring, investigating,
collecting data, and trying out theories
with the hope that at some point,
we'll be able to reach a consensus.
This is what happened with the chemists and physicists.
With his theory of Brownian motion,
Albert Einstein calculated how a very small
but still visible particle would behave
if it was bumping into unseen atoms.
A while later, a French scientist, Jean Baptiste Perrin,
performed the experiment put forth by Einstein,
and the two together provided the direct evidence for atoms
that physicists were seeking.
I've made a video about that experiment,
which I've linked in the description
if you wanna take a look.
A lot of disagreements in science end like this.
As evidence builds, scientists find a way to agree
and a consensus emerges in the community.
But what do we do
when we don't have the luxury of time on our hands?
With the COVID-19 case,
we couldn't afford to wait around for more data
while thousands of people were dying.
A decision needed to be made, fast.
Well, there's no rule book for this situation.
In these cases, there seemed to be further unspoken criteria
guiding the choice of scientists,
separate to those put forward by Kuhn.
According to some philosophers,
these further criteria are contextual
and depend on the scientists' values.
They can be ethical, social, political,
environmental, aesthetic, and so on.
A scientist may lean toward a hypothesis
because they think it would help people in poverty,
a sociopolitical value.
Or they may decide to embrace a hypothesis
because it's in some sense elegant,
a cognitive aesthetic value.
When the decision isn't clear,
scientists sometimes let their own subjective moral judgment
sneak in to guide them.
Now, I want to be clear.
I'm not saying that we shouldn't trust
science or scientists.
Science is an enormously successful human enterprise.
I just wanted to point out some specks of gray
in an area that is usually thought of as black and white.
Being aware of our biases
makes us more equipped to eliminate them.
As Jules Verne said in his book,
"Journey to the Center of the Earth,"
"Science, my boy, is made up of mistakes,
but they are mistakes which it is useful to make
because they lead little by little to the truth."
Now I'd like you to take a moment
to think about your own values.
Would you let them interfere with a scientific judgment?
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