I run Sentinel, a team that seeks to anticipate and respond to large-scale risks. You can read our weekly minutes here. I like to spend my time acquiring deeper models of the world, and generally becoming more formidable. I'm also a fairly good forecaster: I started out on predicting on Good Judgment Open and CSET-Foretell, but now do most of my forecasting through Samotsvety, of which Scott Alexander writes:
Enter Samotsvety Forecasts. This is a team of some of the best superforecasters in the world. They won the CSET-Foretell forecasting competition by an absolutely obscene margin, “around twice as good as the next-best team in terms of the relative Brier score”. If the point of forecasting tournaments is to figure out who you can trust, the science has spoken, and the answer is “these guys”.
I used to post prolifically on the EA Forum, but nowadays, I post my research and thoughts at nunosempere.com / nunosempere.com/blog rather than on this forum, because:
But a good fraction of my past research is still available here on the EA Forum. I'm particularly fond of my series on Estimating Value.
My career has been as follows:
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Thanks for mentioning Sentinel. Two points:
I think there is something powerful about noticing who is winning and trying to figure out what the generators for their actions are.
On this specifically:
the most cost effective way a billionaire entrepreneur and major government contractor could get valuable ROI out of an easily-flattered president with overlapping interests was by buying Twitter
This is not how I see it. Buying Twitter and changing its norms was a surprisingly high-leverage intervention in a domain where turning money into power is notoriously difficult. One of the effects, but not the only one, was influencing the outcome of the 2024 US elections.
I am extremely sympathetic to vNM, but think it's not constructive. I think the world is too high-dimensional, and in some sense we are low compute agents in a high compute world. See here for a bit more background.
In practice, I think vNM works as an idealization of the values of a high or infinite compute agent, but because making it constructive is very expensive, sometimes the best action is not to go through with that but to fall back on heuristics or shortcuts, heuristics which you won't be sure of either (again, as low compute agents in a higher complexity world).