A serious reasoning error that is particularly common among educated people is to argue that if a study hasn't been done on a particular question we have 'no data', and therefore no basis on which to form beliefs or act.

This is incorrect and dangerous. 1/

There is almost always a reference class we can use to make a sensible prediction, and often we can reason about the causal mechanism directly.

To see how this is clearly wrong, consider these two extreme cases: 2/
a. Before a vaccine trial is conducted we have 'no data' on how likely it is to work.

But we can estimate the likelihood just fine! To start with we can just check the base rate of all vaccine trials.

What fraction of all vaccine trials in history have had +ve results? 3/
That gives a much better estimate than pure agnosticism.

b. Imagine now that the vaccine trial results have come back positive. But by chance all the vaccines were given in a blue room.

So, will the vaccine still work if given in a red room? I guess we have 'no data'.

4/
So can we say nothing about about whether vaccines work in red rooms?

That is plainly ridiculous — we understand the causal mechanism and it doesn't involve room colour, so in fact we can give a near definitive answer to that question. 5/
I think this confusion is encouraged by people who study a bit of science but never study philosophy of science, so end up with a garbled epistemology — one more peculiar and foolish than whatever they started with. 6/
It is also encouraged by bureaucratized thinking, where the key is to avoid responsibility by never making personal 'judgement calls', and instead robotically following a cover-your-ass process

The error does most damage when we need to move fast in an uncertain environment. 7/
I've been thinking about it this week because I keep reading people on Twitter saying we have 'no data' and no ability to say whether COVID vaccines work after a single dose, because a trial studying a single dose hasn't been conducted.

What complete bollocks! 8/
To start with the Pfizer vaccine shows new infections crashing a week before patients received the second dose.

But even if they didn't, we could look at the base rate among all vaccines — what fraction of all vaccines offer protection for ~6 months after the first dose? 9/
More than half? Less than half? That is super informative!

Furthermore, we know how vaccines work, and people who are experts in immune reactions probably have a trained intuition on how likely one is to get immunity after a first exposure to an antigen. 10/
They'll also have a sense of how strong human immune reactions are to COVID surface proteins as compared to those on other viruses.

If they think one shot will work with 70% probability or 30% probability, that's a big update either way. 11/
Where something hasn't been studied extensively, the resulting probabilities are likely to fall between 20-80% rather than near 0% or 100%.

But that's normal and fine, and they can go in an expected value calculation nonetheless. 12/
(The folks above are separately making an error where they neglect risks in the status quo.

They call giving one dose 'risky' but if we were already planning to give one dose we could equally say two doses is wildly risky — because you only vaccinate half as many people!) 13/
All estimates are subjective probabilities.

No two cases are exactly the same, and we always have to reason from nearby analogies — which means we always have relevant information we can use to guide a decision. 14/
On top of that, inaction or 'going with the default' is as much an action as choosing the alternative!

Either way you're making an implicit estimate about how good the alternative is. 15/
If you go with the default you're not actually remaining agnostic until the 'data' come in — you're actively deciding that the alternative has a lower expected value.

So, don't let people get away with dodging the responsibility to choose using confused philosophy. 16/

More from For later read

The common understanding of propaganda is that it is intended to brainwash the masses. Supposedly, people get exposed to the same message repeatedly and over time come to believe in whatever nonsense authoritarians want them to believe /1

And yet authoritarians often broadcast silly, unpersuasive propaganda.

Political scientist Haifeng Huang writes that the purpose of propaganda is not to brainwash people, but to instill fear in them /2


When people are bombarded with propaganda everywhere they look, they are reminded of the strength of the regime.

The vast amount of resources authoritarians spend to display their message in every corner of the public square is a costly demonstration of their power /3

In fact, the overt silliness of authoritarian propaganda is part of the point. Propaganda is designed to be silly so that people can instantly recognize it when they see it


Propaganda is intended to instill fear in people, not brainwash them.

The message is: You might not believe in pro-regime values or attitudes. But we will make sure you are too frightened to do anything about it.
I shared this on my FB page and asked, can ya really blame him?

I was half kidding. I also assumed someone would think of what I did pretty quickly and waiting for the comment to mention what I assumed was obvious.

The timing. I was sure someone else had thought of it.


But no one did. 20+ comments in people discussed the morality or bad sense or libertarian perspectives. Someone even said I’m thinking about doing that. No one said what I thought was obvious. Have you thought of it? Is it obvious to you?

Here’s a clue...recognize it?


How about this?


The author discusses it with Mike Wallace in 1958

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