Former software developer and investor. Now working on several projects to reduce xrisk from AI.
Elliot Olds
Karma: 279
Thanks for the additional thoughts. I’ll feed in your suggestions when I get some time and make any updates that result from that.
RE: unknown EAs/rationalists, yeah I agree having some of them on the list is valuable. I plan to add some soon if I don’t get enough volunteers.
When people can get on this list for donating 1% or far less of their net worth, it ends up looking like a celebration of capitalism, rather than a celebration of altruism
I don’t see just appearing on the list as inherently a celebration of the person. I think lots of people will judge people on the list negatively based on their % of wealth donated or their cost per life value, and that’s part of the mechanism that would cause people on the list to donate more or donate more effectively.
I would suggest a more impressive list would be public, wealthy individuals who are ranked by % donated
I think if that was the default ranking the list would lose the main thing that distinguishes EA from other efforts to improve the world, which is an emphasis on effectiveness and actual impact. I agree that “spend nontrivial effort trying to do good” is also something that EA encourages. I just added a feature to be able to sort by % of one’s current wealth donated.
I created a standalone page for ALLFED: https://impactlist.xyz/recipient/alliance-to-feed-the-earth-in-disasters
I didn’t have time to do my own analysis and I’m also trying to get ideas for automatic processing of feedback by LLMs, so I let GPT5.6 and Claude Fable analyze this, with some minimal prompting from me.
Here’s my transcript with GPT5.6: https://github.com/impactlist/impactlist/blob/master/docs/ALLFEDChatTranscript-2026-07-25.md
And my transcript with Fable: https://github.com/impactlist/impactlist/blob/master/docs/ALLFEDChatTranscript-ClaudeCode-2026-07-25.md
I’m curious if you have thoughts on how it’d be if you submitted feedback like you’ve done here into some sort of form, the LLMs went back and forth processing it like that, updated the site, and published a transcript like the above. I think if I make it fully automated right now it’d be fairly exploitable due to LLM sycophancy, unless I tried pretty hard to mitigate that.
> “there are many people on the MIRI list who are not on your list and you said you were open to adding people who were not well known”
I’m open to it but I’m thinking it’s best to prioritize by some combo of: people who actively want to be on the list, people with at least a little bit of public reputation even if it’s some niche, and lives saved.
I think adding ~10 ‘unknown’ EAs/rationalists gets the point across to readers that even normal people can have huge impact and can outdo these billionaires, and I’ll likely pick some from the MIRI list and the LessWrong donors list to add soon if I don’t get enough requests from people. But I’m less sure about adding ~70 of them and immediately doubling the size of the list, as it might make the list less interesting for almost everyone to browse through, and there’s a selection bias there. I don’t have a principled policy on this yet, but this concern is why I haven’t asked an LLM to just add everyone on the MIRI list yet.
Yeah I think the chance of widespread adoption is quite low (< 1%?), but worth a shot. Without adoption I don’t think rich people will care much about the rankings themselves (if ~no one else cares about the rankings, then being higher on the list doesn’t help their status). But even without much adoption there’s a chance for a billionaire to see the list and realize that they weren’t thinking about effectiveness enough or in the right way, and become another Moskovitz-like figure.
I’ve been surprised that three of the commenters so far have had this concern that someone like Musk being ranked 26th/73 will make people want to dismiss the list as a whole. One thing I mentioned in the post is wanting to eventually include all the effects of a person on the world rather than just donations. I’m not sure if this would help though, or just open up way more surface area for people to want to dismiss the list because some assumption went against a deeply held belief of theirs.
Thanks!
I agree that ALLFED should not inherit the default disaster relief numbers. Ideally it would have its own analysis, because even if the numbers do end up being similar to AI x-risk, the reasons why would be pretty different. I also think the estimates shouldn’t be influenced by the motivations of donors.
If someone wants to add a custom effectiveness analysis of ALLFED (it looks like CEARCH’s numbers are just for part of the portfolio), that’d be great. Otherwise I plan to eventually get to it.
The curated longtermist assumptions use a growth rate of 0.000002% over 10 billion years with a ceiling of a million times the current population, so the population reaches 8.3 quadrillion after 711 million years. Still probably on the low end if we start colonizing space.
Yeah the LLM driven donation research did find both of those sources and both are used as proof for at least some donations. This wouldn’t have caused people to be added who weren’t already on the list though.
I do count ‘deaths caused’ via donations (the AI capabilities cause area has a negative cost per life saved), but the root of the issue is that I look only at impact via donations and not overall impact via everything a person does. I eventually want to include those things too, but it seemed like too much work for the first version.
I do have a rule which keeps SBF off the list, that I exclude money donated if it was the proceeds of a crime. In that case there’s a pretty clear line that can be drawn.
Do you have a suggestion for a simple policy you’d want me to adopt to deal with general harmful non-donation actions?
Hi Ellie—thanks for the comments.
RE: the default assumptions, for value judgments I agree that I want the defaults to reflect what is common.
For AI existential risk, I think the crux is mostly not about values (at least for the default assumptions, which only consider the next 100 years) but about how the world works. In those cases I’d like the default rankings to present the best estimates possible without trying to skew towards popular beliefs. But there might be some way that I can make it more clear to people what’s happening.
Fair point about the “lives saved” terminology. I could maybe call that column “life equivalents”.
RE: whether creating a life is equivalent to saving a life, I agree this is something that lots of people will have objections to. Possibly I should make the user’s stance on population ethics an explicit global parameter. I think the most typical view can be simulated with custom assumptions by disabling the Population cause area and possibly shortening the time limit. You can even simulate a longtermist with a person-affecting population ethics view by capping the population at close to the current level and setting the time limit very high (along with disabling the Population cause).
I agree that the motivation behind the rich country phrasing is unclear. I’ve added some clarification to the site. The estimate focuses on rich countries because the type of charity it’s trying to compute a cost per life for tends to be a rich country thing. (There’s currently only one recipient in that category.)
Introducing Impact List: a ranking of philanthropists by expected lives saved
I’m working on something similar. See https://impactlist.xyz/ for a very early demo. Don’t take the effectiveness ratings that seriously yet—I’ve just done very shallow research using LLMs so far. The aim is not to measure how wealthy people would be if they never donated to charity, but how much good billionaires have done with their charitable donations.
I originally posted about it on this forum a couple years ago (https://forum.effectivealtruism.org/posts/LCJa4AAi7YBcyro2H/proposal-impact-list-like-the-forbes-list-except-for-impact) but didn’t start working on it seriously until this month.
Currently looking for volunteers (researchers and React devs). Here’s the discord: https://discord.gg/6GNre8U2ta.
A website to crowdsource research for Impact List
Impact List is building up a database of philanthropic donations from wealthy individuals, as a step in ranking the top ~1000 people by positive impact via donations. We’re also building a database of info on the effectiveness of various charities.
It would be great if a volunteer could build a website with the following properties:
-It contains pages for each donor, and for each organization that is the target of donations.
-Pages for donors list every donation they’ve ever made, with the date, target organization, amount, and any evidence that this donation actually happened.
-Pages for target organizations contain some estimate of each component of the ITN framework, as well as evidence for each of these components.
-There is a web form that allows any Internet user to easily submit a new entry into either of these data sources, which can then be reviewed/approved by the operators of Impact List based on the evidence submitted.
Yes, me and a few others but no one full time yet. I plan to start working roughly full time on it in a month.
I recently posted the work items that I need help with in the discord: https://discord.gg/6GNre8U2ta
Thanks for the feedback!
Regarding (a), it doesn’t seem clear to me that conditional on Impact List being wildly successful (which I’m interpreting as roughly the $110B over ten years case), we shouldn’t expect it to account for more than 10% of overall EA outreach impact. Conditional on Impact List accounting for $110B, I don’t think I’d feel surprised to learn that EA controls only $400B (or even $200B) instead of ~$1T. Can you say more about why that would be surprising?(I do think there’s a ~5% chance that EA controls or has deployed $1T within ten years.)
I think (b) is a legit argument in general, although I have a lot of uncertainty about what the appropriate discount should be. This is also highlighting that using dollars for impact can be unclear, and that my EV calculation bucketed money as either ‘ineffective’ or ‘effective’ without spelling out the implications.
A few implications of that:There’s a ‘free parameter’ in the EV calculation that isn’t obvious: the threshold we use to separate effective from ineffective donations. We might pick something like ‘effective = anything roughly as or more effective than current GiveWell top charities’.
That threshold influences whether our probability estimates are reasonable. For instance depending on this threshold someone can object “A 1 in 1000 chance for $110B to be moved to things as effective as GiveDirectly seems reasonable, but 1 in 1000 for $110B to be moved to things as effective as AMF? No way!”
As noted in footnote 4, we assume that the donations in the ‘ineffective’ bucket are so much less effective than the donations in the ‘effective’ bucket that we can ignore them. Alternatively, we can assume that enough of the ‘effective’ donations are far enough above the minimum effectiveness threshold that they at least cancel out all the ineffective donations.
The threshold we pick also determines what it means when we talk about expected value. If we say the expected value of Impact List is $X it means roughly $X being put into things at at least the level of effectiveness of our threshold. We could be underestimating if Impact List causes people to donate a lot to ultra-effective orgs (and it might, if people try hard to optimize their rankings), but I didn’t try to model that.
Given the bucketing and that “$X of value” doesn’t mean “$X put into the most effective cause area”, I think it may be reasonable to not have a discount. Not having a discount assumes that we’ll find enough (or scalable enough) cause areas over the next ten years at least as effective as whatever threshold value we pick that they can soak up an extra ~110B. Although this is probably a lot more plausible to those who prioritize x-risk than to those who think global health will be the top cause area over that period.
Yeah it will be very time intensive.
When we evaluate people who don’t make the list, we can maintain pages for them on the site showing what we do know about their donations, so that a search would surface their page even if they’re not on the list. Such a page would essentially explain why they’re not on the list by showing the donations we know about and which recipients we’ve evaluated vs. those who we’ve assigned default effectiveness values for their category.
I think we can possibly offload some of the research work on people who think we’re wrong about who is on the list, by being very willing to update our data if anyone sends us credible evidence about any donation that we missed, or persuasive evidence about the effectiveness of any org. The existence of donations seems way easier to verify than to discover. Maybe the potential list-members themselves would send us a lot of this data from alt accounts.
I think Impact List does want to present itself as a best-effort attempt at being comprehensive. We’ll acknowledge that of course we’ve missed things, but that it’s a hard problem and no one has come close to doing it better. Combined with our receptivity to submitted data, my guess is that most people would be OK with that (conditional on them being OK with how we rank people who are on the list).
I think even on EA’s own terms (apart from any effects from EA being fringe) there’s a good reason for EAs to be OK with being more stressed and unhappy than people with other philosophies.
On the scale of human history we’re likely in an emergency situation when we have an opportunity to trade off the happiness of EAs for enormous gains in total well-being. Similar to how during a bear attack you’d accept that you won’t feel relaxed and happy while you try to mitigate the attack, but this period of stress is worth it overall. This is especially true if you believe we’re in the hinge of history.
I also mention this in my response to your other comment, but in case others didn’t notice that: my current best guess for how we can reasonably compare across cause areas is to use something like WALYs. For animals my guess is we’ll adjust WALYs with some measure of brain complexity.
In general the rankings will be super sensitive to assumptions. Through really high quality research we might be able to reduce disagreements a little, but no matter what there will still be lots of disagreements about assumptions.
I mentioned in the post that the default ranking might eventually become some blend of rankings from many EA orgs. Nathan has a good suggestion below about using surveys to do this blending. A key point is that you can factor out just the differences in assumptions between two rankings and survey people about which assumptions they find most credible.
I think you highlight something really important at the end of your post about the benefit of making these assumptions explicit.
Agreed. I guess my intuition is that using WALYs for humans+animals (scaled for brain complexity), humans only, and longtermist beings will be a decent enough approximation for maybe 80% of EAs and over 90% of the general public. Not that it’s the ideal metric for these people, but good enough that they’d treat the results as pretty important if they knew the calculations were done well.
Awesome! (Ideopunk and I are chatting on discord and likely having a call tomorrow.)
Yeah, I’ve lately been considering just three options for moral weights: ‘humans only’, ‘including animals’, and ‘longtermist’, with the first two being implicitly neartermist.
It seems like we don’t need ‘longtermist with humans only’ and ‘longtermist including animals’ because if things go well the bulk of the beings that exist in the long run will be morally relevant (if they weren’t we would have replaced them with more morally relevant beings).
I just added this feature.