How to think about the risk of the Covid vaccine like @nntaleb

Nassim is in favor of the vaccine. He explains why in one of his probability lectures.

If you’re still on the fence, or have a friend or family member who is, read this. 🧵
1. Covid offers no “neutral” choice.

On the one hand, there is the risk of getting vaccinated. On the other, there is the risk of getting (and then spreading) Covid.

The error is to use the precautionary principle for the vaccine, but not for Covid.
2. The risk of Covid is well documented. It’s deadly.

What can we say about the risk of the vaccine?

The traditional mistake is to say that something terrible (like cancer) might develop after, for example, 12 years - so we won’t know if vaccines are safe until after that time.
3. Here’s what’s wrong with this reasoning:

First, every person is biologically different.

If it did take 12 years on average after getting vaccinated to develop cancer, some percentage of the vaccinated population would suffer much sooner than that.
4. Second, let’s generously assume that the percentage expected to have developed cancer this early is very small.

The number of doses that have been administered is very large - over 500 million in the US, and over 9 billion globally.
5. Because the number is so large, if the vaccine really did cause cancer after 12 years on average, we would expect to see a noticeable number of people who have developed cancer already.

We have not seen that yet. And that says a lot.
6. Here’s an analogy:

If you go to a casino, it would take a long time (on average) for you to win 8 times in a row.

But if you have billions of people playing, somebody would win 8 times in a row every day.
7. This is how having a large sample size allows us to reason about undesirable outcomes that are expected (on average) to take a long time to show.

You don't have to wait long to draw inferences if many people are "in the game" - vaccinated.
8. At this point you might say, “All this sounds fine for older people, but I’m in a low-risk category. I’m just not that worried about getting Covid.”

The problem with that way of thinking is that Covid doesn’t just affect you.
9. By contracting the virus, you cause more (expected) deaths than your own.

This is in marked contrast to what happens when you choose not to wear your seatbelt.

The choice of whether or not to get vaccinated affects your neighbors - including the vulnerable.
10. So many people have received the vaccine that we know a lot about possible bad outcomes.

Even those that we would expected to result (on average) many years in the future.

What we know gives us more confidence: vaccines are saving lives.
11. I’ve used this line of reasoning with vaccine-hesitant friends and family.

People who are genuinely hesitant based on perceived risk (and not emotionally or ideologically opposed) tend to be persuaded by it.
12. This thread is based on Nassim’s wonderful lecture from his probability series explaining how to think about vaccine risk.

13. I wrote this thread because the information is so important and some people absorb information better by reading than by watching a lecture.

In that vein, here is my summary of previous lectures in Nassim’s probability series:

14. And here is a link to the series itself. I can’t recommend it highly enough.

Thank you, as always, to @nntaleb for sharing!

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Dec 30, 2021
@nntaleb's brilliant lecture series on probability:

Inferences drawn based on observations of a fat-tailed distribution will fail out of sample - which is to say, in the future.

The lessons here are so important that I’m sharing my notes. 🧵👇

youtube.com/playlist?list=…
1. The Law of Large Numbers (LLN) states that sample mean converges to distribution mean for n large. The problem is that we live in the preasymptotic real world - before “n large.” In particular, n is never large enough in Extremistan.
2. Mediocristan vs. Extremistan: In Mediocristan, tail events are the result of many moderate events. If you find two people with a combined height of 13 feet, the most likely combination is 6’6” and 6’6”.
Read 13 tweets

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