I am an independent research and programmer working at my own consultancy, Shapley Maximizers ÖU. 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. And I haven't left the forum entirely: I remain subscribed to its RSS, and generally tend to at least skim all interesting posts.
I used to do research around longtermism, forecasting and quantification, as well as some programming, at the Quantified Uncertainty Research Institute (QURI). At QURI, I programmed Metaforecast.org, a search tool which aggregates predictions from many different platforms, which I still maintain. I spent some time in the Bahamas as part of the FTX EA Fellowship. Previously, I was a Future of Humanity Institute 2020 Summer Research Fellow, and then worked on a grant from the Long Term Future Fund to do "independent research on forecasting and optimal paths to improve the long-term." I used to write a Forecasting Newsletter which gathered a few thousand subscribers, but I stopped as the value of my time rose. I also generally enjoy winning bets against people too confident in their beliefs.
Before that, I studied Maths and Philosophy, dropped out in exasperation at the inefficiency, picked up some development economics; helped implement the European Summer Program on Rationality during 2017, 2018 2019, 2020 and 2022; worked as a contractor for various forecasting and programming projects; volunteered for various Effective Altruism organizations, and carried out many independent research projects. In a past life, I also wrote a popular Spanish literature blog, and remain keenly interested in Spanish poetry.
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Nice consideration, we hadn't considered non-natural asteroids here. I agree this is a consideration as humanity reaches for the stars, or the rest of the solar system.
If you've thought about it a bit more, do you have a sense of your probability over the next 100 years?
To nitpick on your nitpick, in the US, 1000x safer would be 42 deaths yearly. https://en.wikipedia.org/wiki/Motor_vehicle_fatality_rate_in_U.S._by_year
For the whole world, it would just be above 1k. https://en.wikipedia.org/wiki/List_of_countries_by_traffic-related_death_rate#List, but 2032 seems like an ambitious deadline for that.
In addition, it does seem against the spirit of the question to resolve positively solely because of reducing traffic deaths.
To me this looks like circular reasoning: this example supports my conceptual framework because I interpret the example according to the conceptual framework.
Instead, I notice that Stockfish in particular has some salient characteristics that go against the predictions of the conceptual framework:
Now, does this even matter for considering whether a superintelligence would trade, wouldn't trade? Not that much, it's a weak consideration. But insofar as it's a consideration, does it really convince someone who doesn't already but the frame? Not to me.
This is importantly wrong because the example is in the context of an analogy
getting some pawns : Stockfish : Stockfish's goal of winning the game :: getting a sliver of the Sun's energy : superintelligence : the superintelligence's goals
The analogy is presented as forceful and unambiguous, but it is not. It's instead an example of a system being grossly more capable than humans in some domain, and not opposing a somewhat orthogonal goal
Incidentally you have a typo on "pawn or too" (should be "pawn or two"), which is worrying in the context of how wrong this is.
There is no equally simple version of Stockfish that is still supreme at winning at chess, but will easygoingly let you take a pawn or too. You can imagine a version of Stockfish which does that -- a chessplayer which, if it's sure it can win anyways, will start letting you have a pawn or two -- but it's not simpler to build. By default, Stockfish tenaciously fighting for every pawn (unless you are falling into some worse sacrificial trap), is implicit in its generic general search through chess outcomes.
The bolded part (bolded by me) is just wrong man, here is an example of taking five pawns: https://lichess.org/ru33eAP1#35
Edit: here is one with six. https://lichess.org/SL2FnvRvA1UE
you will not find it easy to take Stockfish's pawns
Seems importantly wrong, in that if your objective is to take a few pawns (say, three), you can easily do this. This seems important in the context that it's hard to to obtain resources from an adversary that cares about things differently.
In the case of stockfish you can also rewind moves.
I disagree with the 5% of switching to a Sundar Pichai hairs simile:
Maybe you could address these problems, but could you do so in a way that is "computationally cheap"? E.g., for forecasting on something like extinction, it is much easier to forecast on a vague outcome than to precisely define it.