Helping high-impact orgs can be high-impact.
Whether that is through IT, HR, or providing food.
Not everyone needs to be a high-level researcher, and I think it is fine to list jobs that have very different skill requirements than the typical 80k-advertized job.
Is there a reason why you are focusing on compute and not salaries? The example numbers you use are rather low compared to the yearly salary of a single AIS researcher.
If you and me and all of humanity gets killed by AI and turned into paperclips, that would be an unprecedented moral catastrophe. If the AIs that killed all of us stay around and enjoy having more paperclips, that is still extremely bad. The very act of killing us makes these AIs not a worthy successor of the human species.
This suggests that proposing to pause AI today is like proposing to pause electricity in 1880
The prospect of AI killing all of us makes these very different. Yes, in both cases a pause will probably slow GDP growth. But humans should be willing to accept lower GDP if this notably reduces the chance of all humans being killed.
warning the Tesla founder his wealth would go to “left-wing nonprofits that will be chosen by Bill Gates.”
Am I missing something or does this argument make no sense? As far as I can tell, Musk can easily fulfill his giving pledge by giving to his preferred not-left-wing nonprofits without deferring to Bill Gates.
I’d genuinely welcome feedback on whether the formalization bottleneck resonates as a priority here
It is not clear from your post why getting more people to contribute to mathlib is good for AI safety.
So far, it sounds like this is more about the AI safety risks from AI being dumb rather than AI being smart. The latter is more important for existential risk, but maybe you mean non-xrisk safety?
Suppose you have a math AI that spits out lean proofs, what would you use it for? Which mathematical questions would you like it to tackle?
I would also note that there are already some math AI startups such as Axiom and Harmonic, who also do Lean (and they don’t seem to be about AI safety at all). EA often focuses on things that are neglected, and it is not clear why non-profit money is needed for the same goals.
I don’t want to be too discouraging, Lean could be useful somehow for reducing AI xrisk, but imo you haven’t made the case.
I think there are many flaws in this post:
comparing changes in probabilities with changes on a 100-point scale doesn’t make sense
“as users realize they can leave their money in a high-yield savings account” doesn’t apply to manifold or metaculus
metaculus is not really prediction markets and manifold markets are not polls (there are polls on manifold, but that is a different thing).
The end of democracy market was not at 23% at Oct 8, 2025, but rather in the 40′s. Perhaps this is an AI hallucination?
For markets that are closer to 0%, you say that long-horizon markets are systematically overpriced, but your overall argument seems to be that these markets underestimate democratic decline and are thus underpriced.
Of the three platforms hosting the markets tracked in this post, only Polymarket has taken direct action on the long-horizon problem, introducing a 4% annualized yield on long-term political and geopolitical positions in September 2025. Manifold’s play-money structure and Metaculus’s reputation-based system have no equivalent mechanism to address opportunity cost mispricing, and given their design, likely never will.
This is wrong, as metaculus avoids the opportunity cost mispricing entirely by not requiring currency for making predictions. And manifold had a loan system for a long time.
Overall, I find the confident tone and bold phrases such as avoid looking to prediction markets off-putting.
I think forum users should not upvote posts like this that frankly look like AI slop to me.
I don’t think so.
Some less tribalistic hypotheses I can think of:
EAs concerned about animal welfare have typically focused on farmed animals, as opposed to animal testing, because of the much larger scale of the suffering
EAs mostly haven’t heard of it.
Maybe some EAs have heard about it, but they don’t think it is worth the effort to write a post about it.
But tribalistic explanations could be a factor too (e.g. MAHA has anti-science vibes, and EAs like to stay on the pro-science side).
(This is probably not the most constructive feedback, but my initial reaction to this short form was that it felt like a right-wing analog of left-wing “Why don’t the EAs tweet about Gaza?”-style criticisms).
I think halting undecidability and Rice’s theorem are being misapplied here. It is true that no algorithm can determine, for every possible program and input, whether that program will halt. But for specific programs and inputs, it is often possible to figure out whether they halt or not.
I agree that there is no method that allows us to check all possible AGI designs for a specific nontrivial behavioral property. But this does not forbid us to select an AGI design for which we can prove that it has a specific behavioral property!
Can you say more on why you think a 1:24 ratio is the right one (as opposed to lower or higher ratios)? And how might this ratio differ for people who have different beliefs than you, for example about xrisk, LTFF, or the evilness of these companies?
I do not recall seeing this usage in AI safety or LW circles. Can you link to examples?
Once upon a time, some people were arguing that AI might kill everyone, and EA resources should address that problem instead of fighting Malaria. So OpenPhil poured millions of dollars into orgs such as EpochAI (they got 9 million). Now 3 people from EpochAI created a startup to provide training data to help AI replace human workers. Some people are worried that this startup increases AI capabilities, and therefore increases the chance that AI will kill everyone.
However, a model trained to obey the RLHF objective will expect negative reward if decided taking over the world
If an AI takes over the world there is no-one around to give it a negative reward. So the AI will not expect a negative reward for taking over the world
The issue is not whether the AI understands human morality. The issue is whether it cares.
The arguments from the “alignment is hard” side that I was exposed to don’t rely on the AI misinterpreting what the humans want. In fact, superhuman AI assumed to be better at humans at understanding human morality. It still could do things that go against human morality. Overall I get the impression you misunderstand what alignment is about (or maybe you just have a different association to words as “alignment” than me).
Whether a language model can play a nice character that would totally give back the dictatorial powers after takeover is barely any evidence whether the actual super-human AI system will step back from its position of world dictator after it has accomplished some tasks.
How is that better than individuals just donating to wherever they think makes sense on the margin?
I think the comment already addresses that here:
moreover, rule by committee enables deliberation and information transfer, so that persuasion can be used to make decisions and potentially improve accuracy or competence at the loss of independence.
This article has a lot of downvoting (net karma of 39 from 28)
This does not seem to be an unusual amount of downvoting to me. The net karma is even higher than the number of votes!
As a more general point, I think people should worry less about downvotes on posts with a high net karma.
As for existential risk from AI takeover, I don’t think having a self-sustaining civilization on Mars would help much.
If an AI has completed takeover on earth and killed all humans on earth, taking over Mars too does not sound that hard, especially since the human civilization is likely quite fragile. (There might be some edge cases, where you solve the AI control problem well enough to guarantee that all advanced AIs leave Mars alone, but not well enough for AI to leave Australia alone, but I think scenarios like these are extremely unlikely).
For other existential risks, it might be in principle useful, but practically very difficult. Building a self-sustaining city on Mars will take a lot of time and resources. On the scale of centuries, it seems like a viable option though.
At the same time though I don’t think you mean to endorse 1).
I have read or skimmed some of his posts and my sense is that he does endorse 1). But at the same time he says
critics seem to frequently conflate my arguments with other, simpler positions that can be more easily dismissed.
so maybe this is one of these cases and I should be more careful.
A recent comment says that restriction has been lifted and the website will be updated next week: https://forum.effectivealtruism.org/posts/aBkALPSXBRjnjWLnP/announcing-the-q1-2025-long-term-future-fund-grant-round?commentId=FFFMBth8v7WBqYFzP
the AI won’t ever have more [...] capabilities to hack and destroy infrastructure than Russia, China or the US itself.
Having better hacking capability than China seems like a low bar for super-human AGI. The AGI would need to be better at writing and understanding code than a small group of talented humans, and have access to some servers. This sounds easy if you accept the premise of smarter-than-human AGI.
I think applying to EAG makes sense in your position, but do not be too disappointed if your application will not be accepted.
I recommend applying for an EA summit or EAGx too! For example, EAGxSingapore might be a good fit, and it is closer than NYC: https://www.effectivealtruism.org/ea-global/events/eagxsingapore-2026 EAGx and EA summit have a lower bar to entry, and many people first attended an EAGx event before attending an EAG event.
Maybe you should inform yourself a little bit more about EA principles before going there, but you do not need to have expert EA knowledge to attend. Regarding your Oikko project, you should be open-minded when attending EAGx or EAG, maybe other participants will try to convince you to work on completely different projects instead.