If It’s Worth Doing, It’s Worth Doing With Made-Up Statistics
I do not believe that the utility weights I worked on last week – the ones that say living in North Korea is 37% as good as living in the First World – are objectively correct or correspond to any sort of natural category. So why do I find them so interesting?
A few weeks ago I got to go to a free CFAR tutorial (you can hear about these kinds of things by signing up for their newsletter). During this particular tutorial, Julia tried to explain Bayes’ Theorem to some, er, rationality virgins. I record a heavily-edited-to-avoid-recognizable-details memory of the conversation below:
Julia: So let’s try an example. Suppose there’s a five percent chance per month your computer breaks down. In that case… Student: Whoa. Hold on here. That’s not the chance my computer will break down. Julia: No? Well, what do you think the chance is? Student: Who knows? It might happen, or it might not. Julia: Right, but can you turn that into a number? Student: No. I have no idea whether my computer will break. I’d be making the number up. Julia: Well, in a sense, yes. But you’d be communicating some information. A 1% chance your computer will break down is very different from a 99% chance. Student: I don’t know the future. Why do you want to me to pretend I do? Julia: (who is heroically nice and patient) Okay, let’s back up. Suppose you buy a sandwich. Is the sandwich probably poisoned, or probably not poisoned? Student: Exactly which sandwich are we talking about here?
In the context of a lesson on probability, this is a problem I think most people would be able to avoid. But the student’s attitude, the one that rejects hokey quantification of things we don’t actually know how to quantify, is a pretty common one. And it informs a lot of the objections to utilitarianism – the problem of quantifying exactly how bad North Korea shares some of the pitfalls of quantifying exactly how likely your computer is to break (for example, “we are kind of making this number up” is a pitfall).
