EA Infrastructure Fund: Ask us anything!

Making up some random numbers:

• The donors to the fund – 8%
• The grantmakers – 10%
• The rest of the EAIF infrastructure (eg Jonas running everything, the CEA ops team handling ops logistics) – 7%
• The grantee – 75%

This is for a typical grant where someone applies to the fund with a reasonably promising project on their own and the EAIF gives them some quick advice and feedback. For a case of strong active grantmaking, I might say something more like 8% / 30% / 12% / 50%.

This is based on the reasoning that we're quite constrained by promising applications and have a lot of funding available.

(I'd be very interested in your answer if you have one btw.)

(No need for the EAIF folks to respond; I think I would also find it helpful to get comments from other folks)

I'm curious about a set of related questions probing this at a more precise level of granularity.

For example, for the 

$248,300 to Rethink Priorities to allow Rethink to take on nine research interns (7 FTE)

Suppose for the sake of the argument that the RP internship resulted in better career outcomes than the interns counterfactually would have.* For the difference of the impact from the internship vs the next-best-option, what fraction of credit assignment should be allocated to:

• The donors to the fund
• The grantmakers
• The rest of the EAIF infrastructure
• RP for selecting interns and therefore providing a signaling mechanism either to the interns themselves or for future jobs
• RP for managing/training/aiding interns to hopefully excel
• The work of the interns themselves

I'm interested in whether the ratio between the first 3 bullet points has changed (for example, maybe with more $s per grant, donor $s are relatively less important and the grantmaker effort/$ ratio is lower)

I also interested in the appropriate credit assignment (breaking down all Jonas' 75%!) of the last 3 bullet points. For example, if most people see the value of RP's internship program to the interns as primarily via RP's selection methods, then it might make sense to invest more management/researcher time into designing better pre-internship work trials. 

I'm also interested in even more granular takes, but perhaps this is boring to other people.

(I work for RP. I do not speak for the org).


*(for reasons like it a) speeded up their networking, b) tangible outputs from the RP internship allowed them to counterfactually get jobs where they had more impact, c) it was a faster test for fit and made the interns correctly choose to not go to research, saving time, d) they learned actually valuable skills that made their career trajectory go smoother, etc) 

I would personally be pretty down for funding reimbursements for past expenses.

I feel very unsure about this. I don't think my position on this question is very well thought through.

Most of the time, the reason I don't want to make a grant doesn't feel like "this isn't worth the money", it feels like "making this grant would be costly for some other reason". For example, when someone applies for a salary to spend some time researching some question which I don't think they'd be very good at researching, I usually don't want to fund them, but this is mostly because I think it's unhealthy in various ways for EA to fund people to flail around unsuccessfully rather than because I think that if you multiply the probability of the research panning out by the value of the research, you get an expected amount of good that is worse than longtermism's last dollar.

I think this question feels less important to me because of the fact that the grants it affects are marginal anyway. I think that more than half of the impact I have via my EAIF grantmaking is through the top 25% of the grants I make.  And I am able to spend more time on making those best grants go better, by working on active grantmaking or by advising grantees in various ways. And coming up with a more consistent answer to "where should the bar be" seems like a worse use of my time than those other activities.

I think I would rather make 30% fewer grants and keep the saved money in a personal account where I could disburse it later.

(To be clear, I am grateful to the people who apply for EAIF funding to do things, including the ones who I don't think we should fund, or only marginally think we should fund; good on all of you for trying to think through how to do lots of good.)

Speaking just for myself: I don’t think I could currently define a meaningful ‘minimum absolute bar’. Having said that, the standard most salient to me is often ‘this money could have gone to anti-malaria bednets to save lives’. I think (at least right now) it’s not going to be that useful to think of EAIF as a cohesive whole with a specific bar, let alone explicit criteria for funding. A better model is a cluster of people with different understandings of ways we could be improving the world which are continuously updating, trying to figure out where we think money will do the most good and whether we’ll find better or worse opportunities in the future.

Here are a couple of things pushing me to have a low-ish bar for funding: 

• I think EA currently has substantially more money than it has had in the past, but hasn’t progressed as fast in figuring out how to turn that into improving the world. That makes me inclined to fund things and see how they go.
• As a new committee, it seems pretty good to fund some things, make predictions, and see how they pan out. 
• I’d prefer EA to be growing faster than it currently is, so funding projects now rather than saving the money to try to find better projects in future looks good to me.  

Here are a couple of things driving up my bar:

• EAIF gets donations from a broad range of people. It seems important for all the donations to be at least somewhat explicable to the majority of its donors. This makes me hesitant to fund more speculative things than I would be with my money, and to stick more closely to ‘central cases’ of infrastructure building than I otherwise would. This seems particularly challenging for this fund, since its remit is a bit esoteric, and not yet particularly clearly defined. (As evidenced by comments on the most recent grant report, I didn’t fully succeed in this aim this time round.)
• Something particularly promising which I don’t fund is fairly likely to get funded by others, whereas something harmful I fund can’t be cancelled by others, so I want to be fairly cautious while I’m starting out in grant making.

Because the EAIF is aiming to grow the overall resources and capacity for improving the world, one model is simply "is the growth rate greater than zero?" Some of the projects we don't fund to me look like they have a negative growth rate (i.e., in expectation, they won't achieve much, and the money and time spent on them will be wasted), and these should obviously not be funded. Beyond that, I don't think it's easy to specify a 'minimum absolute bar'.

Furthermore, one straightforward way to increase the EA community's resources is through financial investments, and any EA projects should beat that bar in addition to returning more than they cost. (I don't think this matters much in practice, as we're hoping for growth rates much greater than typical in financial markets.)

Answering these thoroughly would be really tricky, but here are a few off-the-cuff thoughts: 

1. Tough to tell. My intuition is 'the same amount as I did' because I was happy with the amount I could grant to each of the recipients I granted to, and I didn't have time to look at more applications than I did. Otoh I could imagine if we the fund had significantly more funding that would seem to provide a stronger mandate for trying things out and taking risks, so maybe that would have inclined me to spend less time evaluating each grant and use some money to do active grant making, or maybe would have inclined me to have funded one or two of the grants that I turned down. I also expect to be less time constrained in future because we won't be doing an entire quarter's grants in one round, and because there will be less 'getting up to speed'.

2. Probably most of these are some bottleneck, and also they interact: 
- I had pretty limited capacity this round, and hope to have more in future. Some of that was also to do with not knowing much about some particular space and the plausible interventions in that space, so was a knowledge constraint. Some was to do with finding the most efficient way to come to an answer.
- It felt to me like there was some bottleneck of great applicants with great proposals. Some proposals stood out fairly quickly as being worth funding to me, so I expect to have been able to fund more grants had there been more of these. It's possible some grants we didn't fund would have seemed worth funding had the proposal been clearer / more specific. 
- There were macrostrategic questions the grant makers disagreed over - for example, the extent to which people working in academia should focus on doing good research of their own versus encourage others to do relevant research. There are also such questions that I think didn't affect any of our grants this time but I expect to in future, such as how to prioritise spreading ideas like 'you can donate extremely cost-effectively to these global health charities' versus more generalised EA principles.  

3. The proportion of good applications was fairly high compared to my expectation (though ofc the fewer applications we reject the faster we can give out grants, so until we're granting to everyone who applies, there's always a sense in which the proportion of good applications is bottlenecking us). The proportion of applications that seemed pretty clearly great, well thought through and ready to go as initially proposed, and which the committee agreed on, seemed maybe lower than I might have expected. 

4. I think I noticed some of each of these, and it's a little tough to say because the better the applicant, the more likely they are to come up with good ideas and also to be well calibrated on their fit with the idea. If I could dial up just one of these, probably it would be quality of idea.
 

5. One worry I have is that many people who do well early in life are encouraged to do fairly traditional things - for example they get offered good jobs and scholarships to go down set career tracks. By comparison, people who come into their own later on (eg late in university) are more in a position to be thinking independently about what to work on. Therefore my sense is that community building in general is systematically missing out on some of the people who would be best at it because it's a kind of weird, non-standard thing to work on. So I guess I lean on the side of too few people interested in EA infrastructure stuff.

Re 1: I don't think I would have granted more

Re 2: Mostly "good applicants with good proposals for implementing good project ideas" and "grantmaker capacity to solicit or generate new project ideas", where the main bottleneck on the second of those isn't really generating the basic idea but coming up with a more detailed proposal and figuring out who to pitch on it etc.

Re 3: I think I would be happy to evaluate more grant applications and have a correspondingly higher bar. I don't think that low quality applications make my life as a grantmaker much worse; if you're reading this, please submit your EAIF application rather than worry that it is not worth our time to evaluate. 

Re 4: It varies. Mostly it isn't that the applicant lacks a specific skill.

Re 5: There are a bunch of things that have to align in order for someone to make a good proposal. There has to be a good project idea, and there has to be someone who would be able to make that work, and they have to know about the idea and apply for funding for it, and they need access to whatever other resources they need. Many of these steps can fail. Eg probably there are people who I'd love to fund to do a particular project, but no-one has had the idea for the project, or someone has had the idea for the project but that person hasn't heard about it or hasn't decided that it's promising, or doesn't want to try it because they don't have access to some other resource. I think my current guess is that there are good project ideas that exist, and people who'd be good at doing them, and if we can connect the people to the projects and the required resources we could make some great grants, and I hope to spend more of my time doing this in future.

1. How much do you think you would've granted in this recent round if the total funding available to the IF had been ~$5M? ~$10M? ~$20M?

I can't think of any specific grant decision this round for which I think this would have made a difference. Maybe I would have spent more time thinking about how successful grantees might be able to utilize more money than they applied for, and on discussing this with grantees.

Overall, I think there might be a "paradoxical" effect that I may have spent less time evaluating grant applications, and therefore would have made fewer grants this round if we had had much more total funding. This is because under this assumption, I would more strongly feel that we should frontload building the capacity to make more, and larger, higher-value grants in the future as opposed to optimizing the decisions on the grant applications we happened to get now. E.g., I might have spent more time on:

• Generating leads for, and otherwise helping with, recruiting additional fund managers
• Active grantmaking
• 'Structural' improvements to the fund - e.g., improving our discussions and voting methods

On 2, I agree with Buck that the two key bottlenecks - especially if we weight grants by their expected impact - were "Good applicants with good proposals for implementing good project ideas" and "Grantmaker capacity to solicit or generate new project ideas".

I think I've had a stronger sense than at least some other fund managers that "Grantmaker capacity to evaluate applications" was also a significant bottleneck, though I would rank it somewhat below the above two, and I think it tends to be a larger bottleneck for grants that are more 'marginal' anyway, which diminishes its impact-weighted importance. I'm still somewhat worried that our lack of capacity (both time and lack of some abilities) could in some cases lead to a "false negative" on a highly impactful grant, especially due to our current way of aggregating opinions between fund managers.

5. If there are too few applicants, or too few with relevant skills, is this because there are too few of such people interested in EA infrastructure stuff, or because there probably are such people who are interested in that stuff  but they’re applying less often than would be ideal?

I think both of these are significant effects. I suspect I might be more worried than others about "good people applying less often than would be ideal", but not sure.

4. When an application isn't sufficiently high-quality, is that usually due to the quality of the idea, the quality of the applicant, or a mismatch between the idea and the applicant’s skillset (e.g., the applicant does seem highly generally competent, but lacks a specific, relevant skill)?

All of these have happened. I agree with Buck that "applicant lacks a highly specific skill" seems uncommon; I think the cases of "mismatch between the idea and the applicant" are broader/fuzzier.

I don't have an immediate sense that any of them is particularly common.

Re 3, I'm not sure I understand the question and feel a bit confused about how to answer it directly, but I agree with Buck:

I think I would be happy to evaluate more grant applications and have a correspondingly higher bar. I don't think that low quality applications make my life as a grantmaker much worse; if you're reading this, please submit your EAIF application rather than worry that it is not worth our time to evaluate. 

• Fundamental, macrostrategic, basic, or crucial-considerations-like work that could aid in generating project ideas and evaluating applications
  • E.g., it sounds like this would've been relevant to Max Daniel's views on the IIDM working group in the recent round

Hmm, I'm not sure I agree with this. Yes, if I had access to a working crystal ball that would have helped - but for realistic versions of 'knowing more about macrostrategy', I can't immediately think of anything that would have helped with evaluating the IIDM grant in particular. (There are other things that would have helped, but I don't think they have to do with macrostrategy, crucial considerations, etc.)

My knee-jerk reaction is: If "net negative" means "ex-post counterfactual impact anywhere below zero, but including close-to-zero cases" then it's close to 50% of grantees. Important here is that "impact" means "total impact on the universe as evaluated by some omniscient observer". I think it's much less likely that funded projects are net negative by the light of their own proxy goals or by any criterion we could evaluate in 20 years (assuming no AGI-powered omniscience or similar by then).

(I still think that the total value of the grantee portfolio would be significantly positive b/c I'd expect the absolute values to be systematically higher for positive than for negative grants.)

This is just a general view I have. It's not specific to EA Funds, or the grants this round. It applies to basically any action. That view is somewhat considered but I think also at least somewhat controversial. I have discussed it a bit but not a lot with others, so I wouldn't be very surprised if someone replied to this comment saying "but this can't be right because of X", and then I'd be like "oh ok, I think you're right, the close-to-50% figure now seems massively off to me".

--

If "net negative" means "significantly net negative" (though I'm not sure what the interesting bar for "significant" would  be), then I'm not sure I have a strong prior. Glancing over the specific grants we made I feel that for very roughly 1/4 of them I have some vague sense that "there is a higher-than-baseline risk for this being significantly net negative". But idk what that higher-than-baseline risk is as absolute probability, and realistically I think all that's going on here is that for about 1/4 of grants I can easily generate some prototypical story for why they'd turn out to be significantly net negative. I don't know how well this is correlated with the actual risk.

(NB I still think that the absolute values for 'significantly net negative' grants will be systematically smaller than for 'significantly net positive' ones. E.g., I'd guess that the 99th percentile ex-post impact grant much more than offsets the 1st percentile grant [which I'm fairly confident is significantly net negative].)

This isn't what you asked, but out of all the applications that we receive (excluding desk rejections), 5-20% seem ex ante net-negative to me, in the sense that I expect someone giving funding to them to make the world worse. In general, worries about accidental harm do not play a major role in my decisions not to fund projects, and I don't think we're very risk-averse. Instead, a lot of rejections happen because I don't believe the project will have a major positive impact.

As an aside, I think that's an excellent heuristic, and I worry that many EAs (including myself) haven't internalized it enough.

(Though I also worry that pushing too much for it could lead to people failing to notice the exceptions where it doesn't apply.)

My very off-the-cuff thoughts are:

• If it seems like you are in an especially good position to assess that org, you should give to them directly. This could, e.g., be the case if you happened to know the org's founders especially well, or if you had rare subject-matter expertise relevant to assessing that org.
• If not, you should give to a donor lottery.
• If you win the donor lottery, you would probably benefit from coordinating with EA Funds. Literally giving the donor lottery winnings to EA Funds would be a solid baseline, but I would hope that many people can 'beat' that baseline, especially if they get the most valuable inputs from 1-10 person-hours of fund manager time.
• Generally, I doubt that it's good use of the donor's and fund managers' time if donors and fund managers coordinated on $1,000 donations (except in rare and obvious cases). For a donation of $10,000 some very quick coordination may sometimes be useful - especially if it goes to an early-stage organization. For a $100,000 donation, it starts looking "some coordination is helpful more likely than not" (though in many cases the EA Funds answer may still be "we don't really have anything to say, it seems best if you make this decision independently"), but I still don't think explicit coordination should be a strong default or norm.

One underlying and potentially controversial assumption I make is that more variance in funding decisions is good at the margin. This pushes toward more independent funders being good, reducing correlation between the decisions of different funders, etc. - My view on this isn't resilient, and I think I remember that some thoughtful people disagree with that assumption.

Re your 19 interventions, here are my quick takes on all of them

Creating, scaling, and/or improving EA-aligned research orgs

Yes I am in favor of this, and my day job is helping to run a new org that aspires to be a scalable EA-aligned research org.

Creating, scaling, and/or improving EA-aligned research training programs

I am in favor of this. I think one of the biggest bottlenecks here is finding people  who are willing to mentor people in research. My current guess is that EAs who work as researchers should be more willing to mentor people in research, eg by mentoring people for an hour or two a week on projects that the mentor finds inside-view interesting (and therefore will be actually bought in to helping with). I think that in situations like this, it's very helpful for the mentor to be judged as Andrew Grov suggests, by the output of their organization + the output of neighboring organizations under their influence. That is, they should think that one of their key goals with their research interns as having the research interns do things that they actually think are useful. I think that not having this goal makes it much more tempting for the mentors to kind of snooze on the job and not really try to make the experience useful.

Increasing grantmaking capacity and/or improving grantmaking processes

Yeah this seems good if you can do it, but I don't think this is that much of the bottleneck on research. It doesn't take very much time to evaluate a grant for someone to do research compared to how much time it takes to mentor them.

My current unconfident position is that I am very enthusiastic about funding people to do research if they have someone who wants to mentor them and be held somewhat accountable for whether they do anything useful. And so I'd love to get more grant applications from people describing their research proposal and saying who their mentor is; I can make that grant in like two hours (30 mins to talk to the grantee, 30 mins to talk to the mentor, 60 mins overhead). If the grants are for 4 months, then I can spend five hours a week and do all the grantmaking for 40 people. This feels pretty leveraged to me and I am happy to spend that time, and therefore I don't feel much need to scale this up more.

I think that grantmaking capacity is more of a bottleneck for things other than research output.

Scaling Effective Thesis, improving it, and/or creating new things sort-of like it

I don't immediately feel excited by this for longtermist research; I wouldn't be surprised if it's good for animal welfare stuff but I'm not qualified to judge. I think that most research areas relevant to longtermism require high context in order to contribute to, and I don't think that pushing people in the direction of good thesis topics is very likely to produce extremely useful research.

I'm not confident.

Increasing and/or improving EAs’ use of non-EA options for research-relevant training, credentials, testing fit, etc.

The post doesn't seem to exist yet so idk

Increasing and/or improving research by non-EAs on high-priority topics

I think that it is quite hard to get non-EAs to do highly leveraged research of interest to EAs. I am not aware of many examples of it happening. (I actually can't think of any offhand.) I think this is bottlenecked on EA having more problems that are well scoped and explained and can be handed off to less aligned people. I'm excited about work like The case for aligning narrowly superhuman models, because I think that this kind of work might make it easier to cause less aligned people to do useful stuff.

Creating a central, editable database to help people choose and do research projects

I feel pessimistic; I don't think that this is the bottleneck. I think that people doing research projects without mentors is much worse, and if we had solved that problem, then we wouldn't need this database as much. This database is mostly helpful in the very-little-supervision world, and so doesn't seem like the key thing to work on.

Using Elicit (an automated research assistant tool) or a similar tool

I feel pessimistic, but idk maybe elicit is really amazing. (It seems at least pretty cool to me, but idk how useful it is.) Seems like if it's amazing we should expect it to be extremely commercially successful; I think I'll wait to see if I'm hearing people rave about it and then try it if so.

Forecasting the impact projects will have

I think this is worth doing to some extent, obviously; I think that my guess is that EAs aren't as into forecasting as they should be (including me unfortunately.) I'd need to know your specific proposal in order to have more specific thoughts.

Adding to and/or improving options for collaborations, mentorship, feedback, etc. (including from peers)

I think that facilitating junior researchers to connect with each other is somewhat good but doesn't seem as good as having them connect more with senior researchers somehow.

Improving the vetting of (potential) researchers, and/or better “sharing” that vetting

I'm into this. I designed a noticeable fraction of the Triplebyte interview at one point (and delivered it hundreds of times); I wonder whether I should try making up an EA interview.

Increasing and/or improving career advice and/or support with network-building

Seems cool. I think a major bottleneck here is people who are extremely extroverted and have lots of background and are willing to spend a huge amount of time talking to a huge amount of people. I think that the job "spend many hours a day talking to EAs who aren't as well connected as would be ideal for 30 minutes each, in the hope of answering their questions and connecting them to people and encouraging them" is not as good as what I'm currently doing with my time, but it feels like a tempting alternative.

I am excited for people trying to organize retreats where they invite a mix of highly-connected senior researchers and junior researchers to one place to talk about things. I would be excited to receive grant applications for things like this.

Reducing the financial costs of testing fit and building knowledge & skills for EA-aligned research careers

I'm not sure that this is better than providing funding to people, though it's worth considering. I'm worried that it has some bad selection effects, where the most promising people are more likely to have money that they can spend living in closer proximity to EA hubs (and are more likely to have other sources of funding) and so the cheapo EA accommodations end up filtering for people who aren't as promising.

Another way of putting this is that I think it's kind of unhealthy to have a bunch of people floating around trying unsuccessfully to get into EA research; I'd rather they tried to get funding to try it really hard for a while, and if it doesn't go well, they have a clean break from the attempt and then try to do one of the many other useful things they could do with their lives, rather than slowly giving up over the course of years and infecting everyone else with despair.

Creating and/or improving relevant educational materials

I'm not sure; seems worth people making some materials, but I'd think that we should mostly be relying on materials not produced by EAs

Creating, improving, and/or scaling market-like mechanisms for altruism

I am a total sucker for this stuff, and would love to make it happen; I don't think it's a very leveraged way of working on increasing the EA-aligned research pipeline though.

Increasing and/or improving the use of relevant online forums

Yeah I'm into this; I think that strong web developers should consider reaching out to LessWrong and saying "hey do you want to hire me to make your site better".

Increasing the number of EA-aligned aspiring/junior researchers

I think Ben Todd is wrong here. I think that the number of extremely promising junior researchers is totally a bottleneck and we totally have mentorship capacity for them. For example, I have twice run across undergrads at EA Global who I was immediately extremely impressed by and wanted to hire (they both did MIRI internships and have IMO very impactful roles (not at MIRI) now). I think that I would happily spend ten hours a week managing three more of these people, and the bottleneck here is just that I don't know many new people who are that talented (and to a lesser extent, who want to grow in the ways that align with my interests).

I think that increasing the number of people who are eg top 25% of research ability among Stanford undergrads is less helpful, because more of the bottleneck for these people is mentorship capacity. Though I'd still love to have more of these people. I think that I want people who are between 25th and 90th percentile intellectual promisingness among top schools to try first to acquire some specific and useful skill (like programming really well, or doing machine learning, or doing biology literature reviews, or clearly synthesizing disparate and confusing arguments), because they can learn these skills without needing as much mentorship from senior researchers and then they have more of a value proposition to those senior researchers later.

Increasing the amount of funding available for EA-aligned research(ers)

This seems almost entirely useless; I don't think this would help at all.

discovering, writing, and/or promoting positive case studies

Seems like a good use of someone's time.

---------------

This was a pretty good list of suggestions. I guess my takeaways from this are:

• I care a lot about access to mentorship
• I think that people who are willing to talk to lots of new people are a scarce and valuable resource
• I think that most of the good that can be done in this space looks a lot more like "do a long schlep" than "implement this one relatively cheap thing, like making a website for a database of projects".

Thanks, this is useful!

Some key uncertainties for me are: 

• What products and clusters of ideas work as 'stepping stones' or 'gateways' toward (full-blown) EA [or similarly 'impactful' mindsets]?
  • By this I roughly mean: for various products X (e.g., a website providing charity evaluations, or a book, or ...), how does the unconditional probability P(A takes highly valuable EA-ish actions within their next few years) compare to the conditional probability P(A takes highly valuable EA-ish actions within their next few years | A now encounters X)?
  • I weakly suspect that me having different views on this than other fund managers was perhaps the largest source of significant disagreements with others.
  • It tentatively seems to me that I'm unusually optimistic about the range of products that work as stepping stones in this sense. That is, I worry less if products X are extremely high-quality or accurate in all respects, or agree with typical EA views or motivations in all respects. Instead, I'm more excited about increasing the reach of a wider range of products X that meet a high but different bar of roughly 'taking the goal of effectively improving the world seriously by making a sincere effort to improve on median do-gooding by applying evidence-based reasoning, and delivering results that are impressive and epistemically useful to someone previously only exposed to median do-gooding' - or at least conveying information, or embodying a style of reasoning about the world, that is important for such endeavours.
    • To give a random example, I might be fairly excited about assigning Steven Pinker's The Better Angels of Our Nature as reading in high school, even though I think some claims in this book are false and that there are important omissions.
    • To give a different example (and one we have discussed before), I'm fairly optimistic about the impact of journalistic pieces like this one, and would be very excited if more people were exposed to it. From an in-the-weeds research perspective, this article has a number of problems, but I basically don't care about them in this context.
    • Yet another example: I'm fairly glad that we have content on the contributions of different animal products to animal suffering (e.g. this or this) even though I think that for most people changing their diet is not among the most effective things they can do to improve the world (or even help farmed animals now).
  • (Though in some other ways I might be more pessimistic / might have a higher bar for such content. E.g., I might care more about content being well written and engaging.)
  • I think my underlying inside-view model here is roughly:
    • One of the highest-leverage effects we can have on people is to 'dislodge' them from a state of complacency or fatalism about their ability to make a big positive contribution to the world.
    • To achieve this effect, it is often sufficient to expose people to examples of other people seriously trying to make a big positive contribution to the world while being guided by roughly the 'right' methods (e.g. scientific mindset), and are doing so in a way that seems impressive to the person exposed.
      • It is helpful if these efforts are 'successful' by generic lights, e.g., produce well-received output.
      • It doesn't matter that much if a 'core EA' would think that, all things considered, these efforts are worthless or net negative because they're in the wrong cause area or miss some crucial consideration or whatever.
• How can we structure the EA community in such a way that it can 'absorb' very large numbers of people while also improving the allocation of talent or other resources?
  • I am personally quite unsatisfied with many discussions and standard arguments around "how much should EA grow?" etc. In particular, I think the way to mitigate potential negative effects of too rapid or indiscriminate growth might not be "grow more slowly" or "have a community of uniformly extremely high capability levels" but instead: "structure the community in such a way that selection/screening and self-selection push toward a good allocation of people to different groups, careers, discussions, etc.".
    • ETA: Upon rereading, I worry that the above can be construed as being too indiscriminately negative about discussions on and efforts in EA community building. I think I'm mainly reporting my immediate reaction to a diffuse "vibe" I get from some conversations I remember, not to specific current efforts by people thinking and working on community building strategy full-time (I think often I simply don't have a great understanding of these people's views).
  • I find it instructive to compare the EA community to pure maths academia, and to large political parties.
    • Making a research contributions to mature fields of pure maths is extremely hard and requires highly unusual levels of fluid intelligence compared to the general population. Academic careers in pure maths are extremely competitive (in terms of, e.g., the fraction of PhDs who'll become tenured professors). A majority of mathematicians will never make a breakthrough research contribution, and will never teach anyone who makes a breakthrough research contribution. But in my experience mathematicians put much less emphasis on only recruiting the very best students, or on only teaching maths to people who could make large contributions, or on worrying about diluting the discipline by growing too fast or ... And while perhaps in a sense they put "too little" weight on this, I also think they don't need to put as much weight on this because they can rely more on selection and self-selection: a large number of undergraduates start, but a significant fraction will just realize that maths isn't for them and drop out, ditto at later stages; conversely, the overall system has mechanism to identify top talent and allocate it to the top schools etc.
      • Example: Srinivasa Ramanujan was, by some criteria, probably the most talented mathematician of the 20th century, if not more. It seems fairly clear that his short career was only possible because (1) he went to a school that taught everyone the basics of mathematics and (2) later he had access to (albeit perhaps 'mediocre') books on advanced mathematics: "In 1903, when he was 16, Ramanujan obtained from a friend a library copy of A Synopsis of Elementary Results in Pure and Applied Mathematics, G. S. Carr's collection of 5,000 theorems.^[14]:39[20] Ramanujan reportedly studied the contents of the book in detail.^[21] The book is generally acknowledged as a key element in awakening his genius.^[21]"
      • I'm not familiar with Carr, but the brevity of his Wikipedia article suggests that, while he taught at Cambridge, probably the only reason we remember Carr today is that he happened to write a book which happened to be available in some library in India.
      • Would someone like Carr have existed, and would he have written his Synopsis , if academic mathematics had had an EA-style culture of fixating on the small fraction of top contributors while neglecting to build a system that can absorb people with Carr-levels of talent, and that consequently can cast a 'wide net' that exposes very large numbers of people to mathematics and an opportunity to 'rise through its ranks'?
    • Similarly, only a very small number of people have even a shot at, say, becoming the next US president. But it would probably still be a mistake if all local branches of the Democratic and Republican parties adopted an 'elitist' approach to recruitment and obsessed about only recruiting people with unusually good ex-ante changes of becoming the next president.
    • So it seems that even though these other 'communities' also face, along some metrics, very heavy-tailed ex-post impacts, they adopt a fairly different approach to growth, how large they should be, etc. - and are generally less uniformly and less overtly "elitist". Why is that? Maybe there are differences between these communities that mean their approaches can't work for EA.
      • E.g., perhaps maths relies crucially on there being a consensus of what important research questions are plus it being easy to verify what counts as their solution, as well as generally a better ability to identify talent and good work that is predictive of later potential. Maybe EA is just too 'preparadigmatic' to allow for something like that.
      • Perhaps the key difference for political parties is that they have higher demand for 'non-elite' talent - e.g., people doing politics at a local level and the general structural feature that in democracies there are incentives to popularize one's views to large fractions of the general population.
      • But is that it? And is it all? I'm worried that we gave up too early, and that if we tried harder we'd find a way to create structures that can accommodate both higher growth and improve the allocation of talent (which doesn't seem great anyway) within the community, despite these structural challenges.
• How large are the returns on expected lifetime impact as we move someone from "hasn't heard of EA at all" toward "is maximally dedicated and believes all kinds of highly specific EA claims including about, e.g., top cause areas or career priority paths"?
  • E.g., very crudely, suppose I can either cause N people to move from '1% EA' to '10% EA' or 1 person from '50% EA' to '80% EA'. For which value of N should I be indifferent?
    • This is of course oversimplified - there isn't a single dimension of EA-ness. I still feel that questions roughly like this one come up relatively often.
  • A related question roughly is: if we can only transmit, say, 10% of the 'full EA package', what are the most valuable 10%? A pitch for AMF? The Astronomical Waste argument? Basic reasons for why to care about effectiveness when doing good? The basic case for worrying about AI risk?  Etc.
  • Note that it could turn out that moving people 'too far' can be bad - e.g., if common EA claims about top cause areas or careers were wrong, and we were transmitting only current 'answers' to people without giving them the ability to update these answers when it would be appropriate.
• Should we fund people or projects? I.e., to what extent should we provide funding that is 'restricted' to specific projects or plans versus, at least for some people, give them funding to do whatever they want? If the latter, what are the criteria for identifying people for whom this is viable?
  • This is of course a spectrum, and the literal extreme of "give A money to do whatever they want" will very rarely seem correct to me.
  • It seems to me that I'm more willing than some others to move more toward 'funding people', and that when evaluating both people and projects I care less about current "EA alignment" and less about the direct, immediate impact - and more about things like "will providing funding to do X cause the grantee to engage with interesting ideas and make valuable learning experiences".
• How can we move both individual grantees as well as the community as a whole more toward an 'abundance mindset' as opposed to 'scarcity mindset'?
  • This is a pretty complex topic, and an area that is delicate to navigate. As EA has perhaps witnessed in the past, naive ways of trying to encourage an "abundance mindset" can lead to a mismatch of expectations (e.g., people expecting that the bar for getting funding is lower than it in fact is), negative effects from poorly implemented or badly coordinated new projects, etc. - I also think there are other reasons for caution against 'being too cavalier with money', e.g., it can lead to a lack of accountability.
  • Nevertheless, I think it would be good if more EAs internalized just how much total funding/capital there would be available if only we could find robustly good ways to deploy it at large scale. I don't have a great solution, and my thoughts on the general issue are in flux, but, e.g., I personally tentatively think that on the margin we should be more willing to provide larger upfront amounts of funding to people who seem highly capable and want to start ambitious projects.
  • I think traditional "nonprofit culture" unfortunately is extremely unhelpful here b/c it encourages risk aversion, excessive weight on saving money, etc. - Similarly, it is probably not helpful that a lot of EAs happen to be students or are otherwise have mostly experienced money being a relatively scarce resource in their personal lives.

Here are a few things: 

• What proportion of the general population might fully buy in to EA principles if they came across them in the right way, and what proportion of people might buy in to some limited version (eg become happy to donate to evidence backed global poverty interventions)? I’ve been pretty surprised how much traction ‘EA’ as an overall concept has gotten. Whereas I’ve maybe been negatively surprised by some limited version of EA not getting more traction than it has. These questions would influence how excited I am about wide outreach, and about how much I think it should be optimising for transmitting a large number of ideas vs simply giving people an easy way to donate to great global development charities.
• How much and in which cases research is translated into action. I have some hypothesis that it’s often pretty hard to translate research into action. Even in cases where someone is deliberating between actions and someone else in another corner of the community is researching a relevant consideration, I think it’s difficult to bring these together. I think maybe that inclines me towards funding more ‘getting things done’ and less research than I might naturally be tempted to. (Though I’m probably pretty far on the ‘do more research’ side to start with.) It also inclines me to fund things that might seem like good candidates for translating research into action.
• How useful influencing academia is. On the one hand, there are a huge number of smart people in academia, who would like to spend their careers finding out the truth. Influencing them towards prioritising research based on impact seems like it could be really fruitful. On the other hand, it’s really hard to make it in academia, and there are strong incentives in place there, which don’t point towards impact. So maybe it would be more impactful for us to encourage people who want to do impactful work to leave academia and be able to focus their research purely on impact. Currently the fund managers have somewhat different intuitions on this question.

We recently transferred a lot of the 'best practices' that each fund (especially the LTFF) discovered to all the other funds, and as a result, I think it's very similar and there are at most minor differences at this point.

I think you meant EAIF, not AWF :)

I think I often have an implicit intuition about something like "how heavy-tailed is this grant?". But I also think most grants I'm excited about are either at least somewhat heavy-tailed or aimed at generating information for a decision about a (potentially heavy-tailed) future grant, so this selection effect will reduce differences between grants along that dimension.

But I think for less than 1/10 of the grants I think about I will have any explicit quantitative specification of the distribution in mind. (And if I have it will be rougher than a full distribution, e.g. a single "x% of no impact" intuition.)

Generally I think our approaches are more often qualitative/intuitive than quantitative. There are rare exceptions, e.g. for the children's book grant I made a crappy cost-effectiveness back-of-the-envelope calculation just to check if the grant seemed like a non-starter based on this. As far as I remember, that was the only such case this round.

Sometimes we will discuss specific quantitative figures, e.g., the amount of donations a fundraising org might raise within a year. But our approach for determining these figures will then in turn usually be qualitative/intuitive rather than based on a full-blown quantitative model.

I have a pretty strong view that I don't fully trust any single person's judgment (including my own), and that aggregating judgments (through discussion and voting) has been super helpful for the EAIF's, Animal Welfare Fund's (AWF's), and especially the Long-Term Future Fund's (LTFF's) overall judgment ability in the past. E.g., I can recall a bunch of (in my view) net-negative grants that didn't end up being made thanks to this sort of aggregation, and also some that did end up happening – where it ultimately turned out that I was wrong.

I have also heard through the grapevine that previous experiments in this direction didn't go very well (mostly in that the 'potential benefits' you listed didn't really materialize; I don't think anything bad happened). Edit: I don't give a lot of weight to this though; I think perhaps there's a model that works better than what has been tried in the past.

I also think that having more discussion between grantmakers seems useful for improving judgment over the longer term. I think the LTFF partly has good judgment because it has discussed a lot of disagreements that generalize to other cases, has exchanged a lot of models/gears, etc.

For this reason, I'm fairly skeptical of any approach that gives a single person full discretion over some funding, and would prefer a process with more engagement with a broader range of opinions of other grantmakers. (Edit: Though others disagree somewhat, and will hopefully share their views as well.)

Our current solution is to appoint guest managers instead, as elaborated on here: https://forum.effectivealtruism.org/posts/ek5ZctFxwh4QFigN7/ea-funds-has-appointed-new-fund-managers

Appointing guest managers takes quite a lot of time, so I'm not sure how many we will have in the future.

Another idea that I think would be interesting is to implement your suggestion with teams of potential grantmakers (rather than individuals), like the Oxford Prioritisation Project. Again it would take some capacity to oversee, but could be quite promising. If someone applied for a grant for a project like this, I'd be quite interested in funding it.

I don't think this has much of an advantage over other related things that I do, like

• telling people that they should definitely tell me if they know about projects that they think I should fund, and asking them why
• asking people for their thoughts on grant applications that I've been given
• asking people for ideas for active grantmaking strategies

Like Max, I don't know about such a policy. I'd be very excited to fund promising projects to support the rationality community, eg funding local LessWrong/Astral Codex Ten groups.

I'm not aware of any such policy, which means that functionally it didn't exist for this round.

I don't know about what policies may have existed before I joined the EAIF, and generally don't have much information about how previous fund managers made decisions. FWIW, I find it hard to believe that there was a policy like the one you suggest, at least for broad construals of 'anything involving'. For instance, I would guess that some staff members working for organizations that were funded by the EAIF in previous rounds might identify at rationalists, and so if this counted as "something involving rationalists" previous grants would be inconsistent with that policy.

It sounds more plausible to me that perhaps previous EAIF managers agreed not to fund projects that primarily aim to build the rationality community or promote standard rationality content and don't have a direct connection to the EA community or EA goals. (But again, I don't know if that was the case.)

Speaking personally, and as is evident from some grants we made this round (e.g. this one), I'm generally fairly open to funding things that don't have an "EA" branding and that contribute to "improving the work of projects that use the principles of effective altruism" (cf. official fund scope) in a rather indirect way. (See also some related thoughts in a different AMA answer.) Standard rationality/LessWrong content is not among the non-EA-branded things I'm generally most excited to promote, but I would still consider applications to that effect on a case-by-case basis rather than deciding based on a blanket policy. In addition, other fund managers might be more generically positive about promoting rationality content or building the rationality community than I am.

My take on this (others at the EAIF may disagree and may convince me otherwise):

I think EA Funds should be spending less time on detailed reports, as they're not read by that many people. Also, a main benefit is people improving their thinking based on reading them (it seems helpful for improving one's judgment ability to be able to read very concrete practical decisions and how they were reached), but there are a many such reports already at this point, such that writing further ones doesn't help that much – readers can simply go back to past reports and read those instead. I think EA Funds should produce such detailed reports every 1-2 years (especially when new fund managers come on board, so interested donors can get a sense of their thinking), and otherwise focus more on active grantmaking.

In addition, I think it would make sense for us to publish reports on whichever topic seems most important to us to communicate about – perhaps an intervention report, perhaps an important but underappreciated consideration, or a cause area. I think this should probably happen on an ad-hoc basis.