Bayesian Mindset
This piece is about the in-practice pros and cons of trying to think in terms of probabilities and expected value for real-world decisions, including decisions that don’t obviously lend themselves to this kind of approach.
The mindset examined here is fairly common in the “effective altruist” and “rationalist” communities, and there’s quite a bit of overlap between this mindset and that of Rationality: A-Z (aka The Sequences), although there are some differing points of emphasis.1 If you’d like to learn more about this kind of thinking, this piece presents a ~20-minute read rather than the >1000 pages of Rationality: A-Z.
This piece is a rough attempt to capture the heart of the ideas behind rationalism, and I think a lot of the ideas and habits of these communities will make more sense if you’ve read it, though I of course wouldn’t expect everyone in those communities to think I’ve successfully done this.
If you’re already deeply familiar with this way of thinking and just want my take on the pros and cons, you might skip to Pros and Cons.
This piece is about the “Bayesian mindset,” my term for a particular way of making decisions. In a nutshell, the Bayesian mindset is trying to approximate an (unrealistic) ideal of making every decision based entirely on probabilities and values, like this:
Should I buy travel insurance for $10? I think there’s about a 1% chance I’ll use it (probability – blue), in which case it will get me a $500 airfare refund (value – red). Since 1% * values = $500, I should not buy it for $10.
(Two more examples below in case that’s helpful.)
The ideal here is called expected utility maximization (EUM): making decisions that get you the highest possible expected value of what you care about.2 (I’ve put clarification of when I’m using “EUM” and when I’m using “Bayesian mindset” in a footnote, but it isn’t ultimately that important.3)
It’s rarely practical to literally spell out all the numbers and probabilities like this. But some people think you should do so when you can, and when you can’t, use this kind of framework as a “North Star” – an ideal that can guide many decisions even when you don’t do the whole exercise.
Others see the whole idea as much less promising.
I think it’s very useful to understand the pros and cons, and I think it’s good to have the Bayesian Mindset as one option for thinking through decisions. I think it’s especially useful for decisions that are (a) important; (b) altruistic (trying to help others, rather than yourself); (c) “unguided,” in the sense that normal rules of thumb aren’t all that helpful.
In the rest of this piece, I’m going to walk through:
Συνέχεια εδώ
Πηγή: cold-takes.com
