The Tale Of Gandhi And The Devil 2021-10-10T13:44:51.412Z
On Scaling Academia 2021-09-20T14:54:31.556Z
Making of #IAN 2021-08-29T16:24:41.391Z


Comment by kirchner.jan on On Scaling Academia · 2021-09-28T12:08:30.099Z · EA · GW

Thank you very much for sharing, I didn't know that platform before! Looks like a great initiative and the science article is also very inspired. The failure mode I see is that they might be aiming too broad - realistically for this to take off you might want to start with a small group of very devoted users who can also benefit from the effort they invest? But finding that group poses a different set of problems, of course.

Regarding the "living wage" argument - thank you for calling me out on that, I crossed the line into science fiction there. 

Comment by kirchner.jan on Solving the moral cluelessness problem with Bayesian joint probability distributions · 2021-03-12T06:25:50.289Z · EA · GW

Interesting! Thank you for writing this, this is something I was also wondering about while reading for the Warwick EA fellowship. My intuition is also that in the case of a "many-membered set of probability functions", I'd define a prior over those and then compute an expected value as if nothing happened. I acknowledge that there is substantial (or even overwhelming) uncertainty sometimes and I can understand the impulse of wanting a separate conceptual handle for that. But it's still "decision making under uncertainty" and should therefore be subsumable under Bayesianism.

I feel similar to ben.smith that I might be completely missing something. But I also wonder if this confusion might just be an echo of the age-old Bayesianism vs Frequentism debate, where people have different intuition about whether priors over probability distributions are a-ok.