What’s left to do but go to the beach?

As we come into the home stretch of our latest series of emails..
(Dealing with risk, uncertainty, and how to think about the Coronavirus pandemic)…

You may have noticed that I’ve been avoiding something.
I’ve been completely mute about a critically important component to understanding your COVID-19 risk:

How risky it actually is.

There hasn’t been a single statistic, figure, fatality rate or case number.

No models.

No predictions.


And this glaring omission is the topic of this email.

I am going to try and make an argument I have been building to for two months now.


We cannot know how risky COVID-19 is…

And trying to find out is only making it worse.

If that sounds like a problematic statement to you, I get it.

All I can ask is that you stick with me through this email.

Let’s start where ALL good philosophical discussions start:

On the internet.

I’d like to share some examples of recent COVID-19 posts I’ve found.

Before I do, a few points:

– It doesn’t matter when these arguments were made.

– I’m not arguing for or against any of the arguments made in these posts.

– These are purely meant as example of rhetoric, so don’t get hung up on any of the numbers they use or don’t use.



All of these posts were made by very smart people.

All of these people are using publicly-available COVID data to make their arguments.

And while I’ve only given you a few quick screenshots, you can tell these people are arguing forcefully and rationally.

These are smart people, being smart.

So let me ask you:

Do you feel smarter?

Now that you’ve read these, do you understand the situation better?

My guess is….


My guess is that you’ve actually read several threads, or posts, or articles like these.

Well-argued, quoting numerous “facts,” dutifully citing their sources…

And you’ve come away with more confused than before.

I know that that’s been my experience.

To dig into why this is the case, we have to take a bit of a journey.

We’re going to start with COVID-19, follow it all the way back to the roots of Western Philosophy, make a hard left into game theory…

And end up back at COVID-19 again.

Let’s start with a (seemingly) basic question:

Why is it so hard for smart people to agree on even basic facts about Coronavirus?

I’m not talking about your Uncle who gets all his news from YouTube because he thinks aliens control the media.

I’m talking smart people with educated backgrounds.

People who understand bias, who understand systems.

How is it possible that even THEY can’t agree on basic things like how dangerous the virus is?

There are two basic categories or problems with understanding Coronavirus:

One is logistical (it’s just really hard to get good information)…

And one is epistemological (it’s just really hard for us to know things, in general).

Let’s start with the first category – logistical.

Gathering accurate data about Coronavirus is extremely difficult.

For one, the size and scale of the outbreak makes this a unique event.

There are very few historical parallels, and none within living memory of most of the people who study this kind of thing.

Two, Coronaviruses (the general family that our current pandemic comes from) are not well understood.

Funding to study them, before the pandemic, was hard to come by.

Not only that, but Coronaviruses are notoriously difficult to grow in lab cultures.

All of this means that only a handful of scientists specialized in Coronaviruses…leaving us woefully unprepared.

On top of a general lack of knowledge, we have to be careful to separate Coronavirus and COVID-19 (the disease that the virus causes).

While Coronavirus doesn’t seem to vary much around the world, COVID-19 does. That’s because the disease effects people differently depending on their unique health risks, the society in which they live, etc.

If you’re overweight, your experience of COVID-19 may be very different than someone who’s not.

Same if the area where you live has a lot of pollution.

Or if you smoke.

Or if you’re above 40.

Or if you’re diabetic.

All this makes the overall impact of the disease extremely hard to predict. We’re not sure what the important risk factors are, or how dramatically they impact the disease’s progression.

Take the fatality rate, for example.

Personally, I’ve seen people claim the fatality rate is as high as 7%, and others say it’s as low as .05%.

Why is this so hard to figure out?

The number we’re talking about is referred to as the “case fatality rate,” or CFR. CFR is the percentage of people diagnosed with COVID-19 who die.

That seems pretty straightforward.

But, as we mentioned above, the disease’s effects vary from country to country.

CFR also changes based on how many people you test, and WHO you test – if you test only people in the emergency room, or people in high-risk demographics, the percentage of fatalities will be higher. If you test everyone on Earth, the percentage of fatalities will be lower.

The CFR will also change based on the quality of treatment; after all, better treatment should result in a better chance of living.

That means that CFR will not only change from country to country, but will change within the same country over time as treatments evolve and testing ramps up.

Based solely on the logistical challenges around understanding an event of this scale, we should expect a great deal of uncertainty.


Our fundamental problem with understanding coronavirus is NOT that we lack data or smart people to help us process that data.

Our problem is that data doesn’t help us at all.

How could this be the case?

If we need to understand something, won’t more data help with that?

This brings us to the second category of problem that I mentioned earlier:

See, the thing that I’ve found so completely fascinating about this pandemic…

Is how directly it brings us out of the routine of our everyday lives…
Right into the domains of Western Philosophy.

What I’m going to argue here is that our struggle to understand coronavirus is directly related to our struggle to understand anything.

See, normally, we get away with not really having to know how we know stuff.

We operate according to “generally accepted best practice” or “custom,” and get along fine.

But Coronavirus is different.

Someone might say, “I just listen to what a majority of epidemiologists say.”

But how do we know which epidemiologist to listen to?

Or how many epidemiologists need to agree to constitute a majority?

Or whether the majority believing something is even evidence that it’s true?

Or whether it’s all a media plot?

We’ve officially left the realm of epidemiology…

And entered the realm of epistemology (the theory of knowledge).

This is why our online arguments over fatality rates go nowhere:

They aren’t about what we know…

They’re about how we know what we know.

And with that, I’d like to introduce you to Karl Popper and Thomas Kuhn.

Karl Popper was a British philosopher who lived from 1902 to 1994.

Popper was an incredibly influential philosopher of science, and I will be the very first to admit that my understanding of his work is limited. I highly encourage you to research Popper on your own, rather than taking my own interpretation of him as fact.

That said, Popper’s primary contribution to my own mental models has been this:

Theories can never be empirically proven, only falsified.

Here’s what that means to me:

We can never be absolutely sure that what we believe corresponds exactly to external reality.

Western Philosophy in general has spent the last 200 years more or less demolishing the idea that we can somehow escape our own mental constructs, sense impressions, and physical limitations to achieve a “God’s-Eye View” of the world as it is.

That doesn’t mean there is no external reality, necessarily; just that we can never be 100% sure that we know exactly what it is.

So, how do we go about gaining knowledge?

Popper argues that we gain knowledge by falsifying beliefs, rather than “proving” them, per se.

Let’s take a hypothetical example:

Say a friend of yours claims that the Dodo is extinct.

This may or may not be “true” in the absolute sense. And, indeed, even if we haven’t seen a Dodo in a century or more, we can’t be absolutely certain, for instance, that there isn’t some cave somewhere with a hidden colony of Dodo.

There remains a possibility, even if it’s small, that the Dodo is not extinct.
However, I can falsify the statement “the Dodo is extinct” very easily, simply by locating a living Dodo.

Thus, knowledge proceeds negatively; not by discovering absolute truths, but by systematically falsifying the untrue.

Knowledge, then, is a process by which we become more and more accurate over time through falsification.

That may seem like it makes sense, but if knowledge is ONLY falsification, why do we feel like we “know” things?

How do some ideas become “accepted wisdom”?

To understand this piece of the puzzle, we come to Thomas Kuhn.

Thomas Kuhn was an American philosopher of science who lived form 1922 to 1996.

Kuhn’s most famous work is the Structure of Scientific Revolutions, in which he proposed a model for understanding how science advances.

Let’s pick up where we left off with Popper.

Popper proposed that knowledge is about finding what isn’t true, a process that becomes more accurate over time…

(even though we can never be 100% sure what we know is right).

Imagine you’re a scientist studying the weather.

You perform several experiments, testing (and often disproving) your hypotheses.

In one experiment, you discover an interesting connection between electrical currents and snowfall in Ohio.

You publish your findings in the prestigious Journal of Ohio Snowfall Studies.

I, upon reading your article, decide to try and replicate your findings.

Upon doing so, I find myself unable to recreate the results that got you so excited.
In fact, MY findings indicate there is 

no connection between electrical currents and Ohio snowfall.

I publish MY findings, which seem to falsify YOUR findings.

A colleague, interested in the resulting debate, then attempts to reconcile the two sets of findings by offering a theory that a third element (blood pressure of nearby raccoons) is actually the cause of the phenomena.

A FOURTH scientist then tries to disprove the Stressed-Out-Racoon Hypothesis…

And so on.

Note that the scientific process described above is largely destructive; it is through gradual falsification that knowledge is being progressed.
Over time, these layers of falsification build up, leaving very few ideas unscathed.

The ideas that are left standing gradually become accepted wisdom. So accepted wisdom is just “all the stuff we haven’t been able to falsify.”

Kuhn’s insight was that just because something is “accepted wisdom” does not mean it is true.

In fact, it is through the accumulation of accepted wisdom that entire eras of scientific progress are overturned.

How is this possible?

Our understanding of the world is never complete. Remember – Popper argues that we can’t ever have a fully accurate, absolutely certain view of the world.

The best we can get are theories that are useful; theories that prove their worth by making the world a better place.

But a theory’s usefulness doesn’t guarantee its accuracy.

For example, I might believe that singing to my plants every day helps them grow.

Now, that theory might be useful; it might encourage me to water the plants every day. It might lower my overall stress levels by getting me to spend time outside.

But that doesn’t mean singing to the plants really helps them grow in and of itself.

Kuhn argued that something similar happens in the sciences. Over time, through experimentation, we find useful ideas; ideas that help us progress.
But because our understanding is always limited, and there is no possibility of being 100% certain, mistakes will always creep in to systems of knowledge we build.

We can’t avoid this; it’s inevitable. Humans make mistakes, and so mistakes are built in to everything that we do.

In science and philosophy, these mistakes manifest as seemingly unsolvable problems, contradictory bits of knowledge, and straight-up weirdness that just doesn’t “fit” what we know “know to be “true.”

In Kuhn’s formulation, when these questions become too much to bear – when the blind spots in our picture of the world become too obvious – a revolution occurs.

This means that the “paradigm” (Kuhn’s word for the scientific consensus of how the world works) becomes undone…and a new paradigm takes its place.

Just as Copernicus replaced the Ptolemaic System…and Newton undermined Copernicus…and the Theory of Relativity destroyed Newton…

So does scientific consensus advance…

By destroying itself.

In other words:

Knowledge is an act of creative destruction.


We’ve gone very high-level here…

So let’s bring this back to Earth:

What does this have to do with Coronavirus?

I’m certainly not arguing that Coronavirus is the herald of a scientific revolution.

The basic tools for understanding what’s happening (epidemiology, statistical analysis, modeling, etc) have been around for a long time.
What I’m arguing is that our attempts to “fix” our knowledge of the virus and to “get it right” are actually making it harder to understand.

Stay with me, now. 🙂

We discussed, above, the idea that science moves forward through a process of creative destruction by systematically falsifying and undermining itself.
Typically, this process is contained within the pages of the various journals and academic conferences of a given field.

Want to debate the current state of genetics? There are designated places to do so.

Want to get into an argument about geology? Figure out where that debate is occurring and get started!

The debate over Coronavirus, though is not happening within the pages of academic journals.

It is not limited to scholarly conferences and meet ups.

It is occurring everywhere at once.

It’s on the internet.

The news.

The paper.



Your friends are discussing it.

Your neighbors bring it up.

Just as the virus itself is endemic (meaning, literally everywhere) so is information about the virus.

Not only is it everywhere, everyone is weighing in.

Epidemiologists? Sure. They’re celebrities now.

But also:

General practitioners, statisticians, politicians, teachers, plastic surgeons, marketers, historians, plumbers, pundits, accountants…

Everyone has an opinion.

When you combine:

Impossibly large amounts of uncertain data….

With an impossibly large amount of people interpreting that data…

You get a massive, exponential increase in the amount of information in the system.

It isn’t that we “don’t know” enough about COVID-19 and the Coronavirus…

It’s that we know too much, and have no way of discerning what’s right.

Let’s return, briefly, to the idea of the common knowledge game that we addressed in “The Beauty Contest” and “Missionaries.”

How could anyone possibly comprehend such a mess of information?

We can’t. It’s impossible.

So…what do we do instead?

We turn to Missionaries.

Missionaries are the people we look to in order to know what other people know.

They’re the news channels, pundits, journalists…the sources, not of “truth,” but of “common knowledge.”

The problem with looking to Missionaries now, however, is that they’re wrong.

And I know they’re wrong, because they have to be wrong.


Logistically, it’s nearly impossible to get a grip on what COVID-19 does. Science is certainly our best option.

But epistemologically, science only advances by undermining itself.
And today, that process is being exponentially multiplied across every possible news outlet, Twitter feed and YouTube channel…

Meaning that all anyone hears…

All anyone sees…

Is missionary after missionary contradicting themselves.

Science is working; don’t get me wrong.

Slowly, but surely, we are getting closer and closer to the truth.
But what we as a culture are perceiving (possibly for the first time in Western Society)

Is just how self-destructive scientific progress actually is.

And while I don’t think we can understand the absolute chaos of COVID-19 information…

do think we can use game theory to predict how people will react to seeing large-scale falsification in progress for the first time.

I think people will simply conclude that no one knows anything, and that worrying about it is too cognitively-taxing.

For fun, I googled “beaches packed” just now.

Here’s the very first article that came up:

When the message gets too chaotic, too impenetrable? People stop listening.
To be clear, I absolutely do not blame anyone who has started tuning COVID-19 out at this point.

Yes, other countries had wildly different approaches, and different outcomes.

Yes, different messaging and different strategies could have prevented countless deaths here in the United States.

But that didn’t happen.

Now, what we’re left with is an impenetrable “fog of pandemic” made exponentially worse by our desire for more information.

In our attempt to understand the virus we have undermined any attempt to address it.

By putting science on display, we have guaranteed our loss of faith in it.

What’s left to do but go to the beach?

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