In his daily coronavirus briefings, President Trump regularly touts the malaria drug hydroxychloroquine as possibly one of the “biggest game changers in the history of medicine”—based on what seems to be a few anecdotal reports of mild benefits in Covid-19 patients.
When a reporter asked Anthony Fauci, director of the National Institute of Allergy and Infectious Diseases, “What is the medical evidence?” Trump stopped him from answering, and at one point said this: “What do I know? I'm not a doctor, but I have common sense.”
Look, I hope the drug turns out to be helpful. But this statement is bad. This kind of thinking is no basis for a public health strategy in a pandemic. I mean, if you look back historically, common sense does not have a great track record against science.
Of course, if there’s a ton of evidence for something politicians don’t want to hear about, like global warming, they’re more fastidious. When researchers say their models are imperfect, climate deniers jump on that and say, therefore, it’s too soon to take action.
It seems like we could all use a little refresher on the nature of science—what it is and what it really does.
Fundamentally, science is the process of building and testing models. When I teach physics, I don’t talk about “laws” of motion; I want students to understand that all of our descriptions of the world—including the ones we bet our lives on, like, say, in designing airplanes or bridges—they are all just models of reality.
If what pops into your head when I say “models” is a little toy version of a ’67 Mustang, good! It’s the same idea. Think about it: That model car maybe isn’t a perfect scale replica, and it doesn’t drive like a car. But if you wanted to convey to someone what a ‘67 Mustang was like, it would be a great help.
Or how about a globe? Yes, that's a physical model of Earth showing the relative positions of the continents. You can learn a lot about the planet’s geography from it but not much about it’s geology, since it’s made of papier-mâché. And here is another important aspect of models: They don't have to show everything—in fact, they can’t. They just have to be useful.
Models don't have to be physical; they can also be mathematical. We can use a logistic function to show the relationship between the number of existing Covid-19 cases and the rate of new infections per day. With a mathematical model, it's easier to see three other aspects of models:
- Models are built with real data from experiments. You have to have data.
- Models can be used to predict stuff—maybe the future number of infected humans or the trajectory of a comet around the sun.
- Models are just models. They aren't the truth. When data contradicts a model, we have to change the model.
So that's it. Science is just the process of building and refining models.
I think of "common sense" as a set of ideas that most humans would agree on without too much debate. But this doesn't work out well in science. The results of experiments often confound our expectations. You can go all the way back to Aristotle. He was an educated dude, and he made a bunch of statements about how the world works that seemed very reasonable, such as:
- Heavy things fall faster than light things.
- If you stop pushing an object, it will slow down and stop moving.
- To make something speed up, you need to push it harder and harder.
When I teach introductory physics, students still begin with these common-sense ideas. But there are very simple experiments to show that they aren't true.
- If you drop two balls of different masses, they hit the ground at the same time.
- A low-friction car on a track travels at a constant velocity with no forces on it.
- Applying a constant force on an object causes it to accelerate.
Even with observational data, we can draw the wrong conclusions. That’s what happened with the geocentric model of the solar system, which had the sun and planets orbiting Earth. If you just go watch the sky, that seems like a reasonable conclusion. I mean, common sense says it doesn't feel like we’re flying through space at over 100,000 kilometers an hour—that’s the speed needed to orbit the sun in one year. But indeed that is what we do with our new and improved heliocentric (sun-centered) model.
What about medicine? Was it common sense to use mold to fight bacterial infections? That wouldn't have been my first idea, but it led to the introduction of penicillin in 1942—a real game changer.
So what about the use of hydroxychloroquine for Covid-19? Doesn't that just make sense? No, that's not how it works. We already know, for starters, that the drug can cause heart failure in some people. You need clinical trials with sufficiently large samples. Since there are many differences from one human to the next, and different environmental factors, you need lots of data to know if something is effective and safe. Medicine is science; it's not common sense.
Oh, since we're on the topic of scientific modeling, I should probably address this tweet by US senator John Cornyn (R-Texas):
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Can models predict the future? Yes. Do they always get it right? No. Does that mean the models are bogus? Not at all. Just consider our models for weather prediction. They're based on stuff like the interaction between the wind and the ground as well as high and low pressures. It's complicated. After that, you have to know the current conditions to be able to predict future conditions. Since you can't actually measure the temperature and pressure everywhere, you don't get a perfect prediction. But just because it doesn't make perfect predictions doesn't mean it's not useful.
Oh, but what about "THE SCIENTIFIC METHOD"? Forget about your middle-school science fair—that list of steps isn't really how we do science. It's much easier to just say that science is the process of building and refining models. That's it. Just like that model of the ’67 Mustang.
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