What I’m reacting to is more the “hot take” version that shows up in EA-adjacent podcasts — often as an analogy when people talk about AI policy: “look at nuclear, it got over-regulated and basically died, so don’t do that to AI.” In that context it’s not argued carefully, it’s just used as a rhetorical example, and (to me) it’s a pretty lossy / misleading compression of what’s going on.
I agree it’s a bit lossy and sometimes reflexive (this is what I meant with relying on libertarian priors), but I am still confused about your argument.
Because the argument you criticize is an historical one (“nuclear over regulation killed nuclear”) which is different from “now we need many steps and there are different strategies to make nuclear more competitive again”.
I think it is basically correct that over-regulation played a huge part in making nuclear uncompetitive and I don’t think that Isabelle or others knowing the history of nuclear energy would disagree with that, even if it might be a bit overglossed / stylized (obviously, it is not the only thing).
Working on climate with an interest in AI, I found this a fascinating read.
But I am a bit left wanting as to what the learnable lessons for the AI community are that will make the AI community act better than the climate community.
Could you articulate this?
(I think a lot of the parallels you cite are true, but I don’t think they offer a lot of actionable implications, they feel more like negative updates on the difficulty of acting wisely for fast-moving coordination problems with deep uncertainty and lots of politicization).