David_Moss

Karma: 10,177

I am the Principal Research Director at Rethink Priorities. I lead our Surveys and Data Analysis department and our Worldview Investigation Team.

The Worldview Investigation Team previously completed the Moral Weight Project and CURVE Sequence / Cross-Cause Model. We’re currently working on tools to help EAs decide how they should allocate resources within portfolios of different causes, and to how to use a moral parliament approach to allocate resources given metanormative uncertainty.

The Surveys and Data Analysis Team primarily works on private commissions for core EA movement and longtermist orgs, where we provide:

Private polling to assess public attitudes
Message testing / framing experiments, testing online ads
Expert surveys
Private data analyses and survey / analysis consultation
Impact assessments of orgs/programs

Formerly, I also managed our Wild Animal Welfare department and I’ve previously worked for Charity Science, and been a trustee at Charity Entrepreneurship and EA London.

My academic interests are in moral psychology and methodology at the intersection of psychology and philosophy.

David_Moss 19 Nov 2025 22:17 UTC
4 points
0 ∶ 0
in reply to: gergo’s comment on: Runway till January: Amplify’s funding ask to market EA & AI Safety
Thanks gergo!

A small number of small orgs do meet the bar, though! AIS Cape town, EA Philippines, EA & AIS Hungary (probably at least some others) has been funded consistently for years. The bar is really high though for these groups, and I guess funders don’t see enough good opportunities to support to justify investing more resources into them through external services. (Maybe this is what you meant anyway but I wasn’t sure)
My claim is actually slightly different (though much closer to your second claim than your first). It’s definitely not that no small groups are funded (obviously untrue), but that funders are often not interested in funding work on the strength of it supporting smaller groups, where “smaller” includes the majority of orgs.

David_Moss 19 Nov 2025 9:54 UTC
9 points
1 ∶ 0
on: Runway till January: Amplify’s funding ask to market EA & AI Safety
The highest counterfactual impact comes from working with organisations that could benefit but haven’t budgeted for marketing due to a lack of understanding.
As JS from Good Impressions told us:
“Willingness to pay is not as strong a predictor of commitment or perceived value as I thought it would be.”
This creates a chicken-and-egg problem: funders expect clients to pay, but clients lack the means.
This matches our own experience (with the Rethink Priorities, Surveys and Data Analysis team).
I would add that, in our experience, the situation is worse than the chicken-and-egg problem as stated. As you note, funders are often not interested in funding work which is supporting smaller, more peripheral or less established groups (and to be clear, this seems to be a matter of ‘most orgs don’t meet the bar’ rather than ‘all but a few smaller groups do meet the bar’).
But we have also been told by more than one funder that if our work is supporting core, well-resourced orgs, then those orgs ought to fund it themselves, and you shouldn’t need central funding.^[1] This creates a real catch-22 situation, where projects of this kind can neither be funded if they are supporting the biggest orgs or if they’re not.
I also find that people often significantly overestimate the ability to pay of even the largest orgs to pay. We often find that orgs are willing to invest tens of staff hours in working with us on a project- implying they value it- but they still have hard limits of whether they can spend $500-1000 on costs for the project.^[2]
1. ^
  I’ve not directly experienced this response recently, as we’ve not been applying for funding on this sort of basis, so YMMV.
2. ^
  Perhaps explained by (i) even well-resourced orgs don’t have large amounts of unrestricted funds that they can spend on whatever unforeseen expenses they want (ii) internal approvals for funding being difficult, (iii) needing/wanting to stick to some, pretty low, sense of what reasonable costs for advertising/experiments are.
What links here?
- Runway till January: Amplify’s funding ask to market EA & AI Safety by gergo (18 Nov 2025 19:22 UTC; 53 points)

[Question] Cause prio cruxes in 2026?

Hayley Clatterbuck11 Nov 2025 15:22 UTC

81 points

30 comments1 min readEA link

David_Moss 10 Nov 2025 10:52 UTC
10 points
0 ∶ 0
on: Lack of Diversity Within EA
I am curious on the communities thoughts on this lack of diversity
In previous surveys, diversity/JEID related issued have often been mentioned as reasons for dissatisfaction. That said, there are diverse views about the topic (many of which you can read here, it’s much discussed).
Community Health Supplementary Survey
EA Survey 2019: Community Information

David_Moss 1 Nov 2025 12:50 UTC
3 points
0 ∶ 0
in reply to: Jakob Lohmar’s comment on: Doing Prioritization Better
Thanks Jakob!
One thing I’ll add to this, which I think is important, is that it may matter significantly how people are engaged in prioritisation within causes. I think it may be surprisingly common for within-cause prioritisation, even at the relatively high sub-cause level, to not help us form a cross-cause prioritization to a significant extent.
To take your earlier example: suppose you have within-animal prioritisers prioritising farmed animal welfare vs wild animal welfare. They go back and forth on whether it’s more important that WAW is bigger in scale, or that FAW is more tractable, and so on. To what extent does that allow us to prioritise wild animal welfare vs biosecurity, which the GCR prioritisers have been comparing to AI Safety? I would suggest, potentially not very much.
It might seem like work that prioritises FAW vs WAW (within animals) and AI Safety vs biosecurity (within GCR), would allow us to compare any of the considered sub-causes to each other. If these ‘sub-cause’ prioritisation efforts gave us cost-effectiveness estimates in the same currency then they might, in principle. But I think that very often:
- Such prioritisation efforts don’t give us cost-effectiveness estimates at all (e.g. they just evaluate cruxes relevant to making relative within-cause comparisons).
- Even if they did, the cost-effectiveness would not be comparable across causes without much additional cross-cause work on moral weights and so on.
- There may be additional incommensurable epistemic differences between the prioritisations conducted within the different causes that mean we can’t combine their prioritisations (e.g. GHD favours more well-evidenced, less speculative things and prioritises A>B, GCR favours higher EV, more speculative things and prioritises C>D).
Someone doing within-cause prioritisation could complain that most of the prioritisation they do is not like this, that it is more intervention-focused and not high-level sub-cause focused, and that it does give cost-effectiveness estimates. I agree that within-cause prioritisation that gives intervention-level cost-effectiveness estimates is potentially more useful for building up cross-cause prioritisations. But even these cases will typically still be limited by the second and third bulletpoints above (I think the Cross-Cause Model is a rare example of the kind of work needed to generate actual cross-cause prioritisations from the ground up, based on interventions).

David_Moss 31 Oct 2025 20:05 UTC
13 points
0 ∶ 0
in reply to: Vasco Grilo🔸’s comment on: Framing EA: ‘Doing Good Better’ Did Worse
Thanks Vasco.
I think there are two distinct questions here: the sample and the analysis.
When resources allow, I think it is often better to draw a representative sample of the full population, and then analyse the effect of different traits / the effects within different sub-populations. Even if the people getting involved in EA have tended to be younger, more educated etc., I think there are still reasons to be concerned about the views of the broader population. Of course, if you are interested in a very niche population then this approach will either not be possible or will be very resources inefficient and you might have to sample more narrowly.
When looking for any interactions with demographics for these results, I found no significant demographic interactions, which is not uncommon. I focus here on the replication study in order to have a cleaner manipulation of the “doing good better” effect, though it’s a smaller sample, and we gathered fewer demographics than in the representative sample in the first study.
For age, we see a fairly consistent effect (the trends are fairly linear even if I allow them to be non-linear, fwiw).
For student status, we see no interaction effect and the same main effect.
For sex, we see no effect and a consistent main effect.^[1]
If there’s a lot of interest this we could potentially look at education and income in the first survey.
1. ^
  People sometimes ask why we use sex rather than gender in public surveys and it’s usually to match the census so that we can weight.

David_Moss 30 Oct 2025 13:04 UTC
6 points
4 ∶ 0
on: Some surprising hiring practices I follow (as a hiring manager and grantmaker in EA)
there’s a limit to how much you can learn in a structured interview, because you can’t adapt your questioning on the fly if you notice some particular strength or weakness of a candidate.
I agree. Very often I think that semi-structured interviews (which has a more or less closely planned structure, with the capacity to deviate), will be the best compromise between fully structured and fully unstructured interviews. I think it’s relatively rare that the benefits of being completely structured outweigh the benefits of at least potentially asking a relevant followup question, and rare that the benefits of being completely unstructured outweigh the benefits of having at least a fairly well developed plan, with key questions to ask going on.

David_Moss 30 Oct 2025 11:22 UTC
4 points
0 ∶ 0
in reply to: Jakob Lohmar’s comment on: Doing Prioritization Better
Thanks Jakob!
For example, there is a lot of discussion on whether we should focus on far future people or present people. This seems to be an instance of CP, but still you could say that the two causes are within the super-ordinate cause of “Human Welfare”.
This is a great example! I think there is a real tension here.
On the one hand, typically we would say that someone comparing near-term human work vs long-term human work (as broad areas) is engaged in cause prioritisation. And the character of the assessment of areas this broad will likely be very much like the character we ascribed to cause prioritisation (i.e. concerning abstract assessment of general characteristics of very broad areas). On the other hand, if we’re classifying the allocation of movement as a whole across different types of prioritisation, it’s clear that prioritisation that was only focused on near-term vs long-term human comparisons would be lacking something important in terms of actually trying to identify the best cause (across cause areas). To give a different example, if the movement only compared invertebrate non-humans vs vertebrate non-humans, I think it’s clear that we’d have essentially given up on cause prioritisation, in an important sense.^[1]
I think what I would say here is something like: the term “cause (prioritisation)” is typically associated with multiple different features, which typically go together, but which in edge cases can come apart. And in those cases, it’s non-obvious how we should best describe the case, and there are probably multiple equally reasonable terminological descriptions. In our system, using just the main top-level EA cause areas, classification may be relatively straightforward, but if you divide things differently or introduce subordinate or superordinate causes, then you need to introduce some more complex distinctions like sub-cause-level within-cause prioritisation.
That aside, I think even if you descriptively divide up the field somewhat differently, the same normative points about the relative strengths and weaknesses of prioritisation focuses on larger or smaller objects of analysis (more cause-like vs more intervention-like) and narrower or wider in scope (within a single area vs across more or all areas), can still be applied in the same way. And, descriptively, it still seems like the the movement still has relatively little prioritisation that is more broadly cross-area.
1. ^
  One thing this suggests is that you might think of this slightly differently when you are asking “What is this activity like?” at the individual level vs asking “What prioritisation are we doing?” at the movement level. A more narrowly focused individual project might be a contribution to wider cause prioritisation. But if, ultimately, no-one is considering anything outside of a single cause area, then we as a movement are not doing any broader cause prioritisation.

EA Survey 2024: Community Satisfaction, Retention & Mental Health

Rethink Priorities29 Oct 2025 12:12 UTC

59 points

0 comments7 min readEA link

David_Moss 28 Oct 2025 14:09 UTC
20 points
4 ∶ 0
in reply to: Davidmanheim’s comment on: Framing EA: ‘Doing Good Better’ Did Worse
Thanks David.
I certainly agree that we should be careful to make sure that we don’t over-optimise short-term appeal at the cost of other things that matter (e.g. long-term engagement, accuracy and fidelity of the message, etc.). I don’t think we’re calling for people to only consider this dimension: we explicitly say that we “think that people should assess particular cases on the basis of all the details relevant to the particular case in question.”
That said, I think that there are many cases where those other dimensions won’t, in fact, be diminished by selecting messages which are more appealing.^[1] For example:
- In some cases, like this one, we’re selecting within taglines that had already been selected as suitable candidates based on other factors (such as accuracy). We’re then additionally considering data on how people actually respond.
- Relatedly, we might have messages available which seem equally good on the other key dimensions which we care about, but which we know to have higher appeal. For example, in this case, I think “the most good you can do” is at least as accurate and likely to encourage long-term engagement as “doing good better”. So, if this phrasing performs better in terms of initially appealing to people, this is a pro tanto consideration in its favour.
- In many contexts, we are only considering the question of which ~5 word tagline to include on a website. So the common tradeoff between shorter, more initially appealing messages and longer but higher-fidelity ones may not apply.
- In some cases, like short website taglines, most of the effect of the messages may be whether the person continues reading at all (in which case they read the rest of the website and learn a lot more content) or whether they are instantly turned off. We might not expect the short taglines to have a long-term effect on people’s understanding of EA (dominating all the later content they read) themselves.
- While initial appeal and long-term engagement could diverge, in many cases, there’s no particular reason to think that they do. This framing suggests a tradeoff between what is merely superficially appealing vs what promotes long-term engagement. But, often, one message might just appeal less to people simpliciter, e.g. because people find it confusing or off-putting, without promoting any longterm benefits.
- More generally, I think that we can often think of plausible ways that a message might appear more appealing, but actually be sub-optimal, when taking into account long-term second order effects or divergent effects across different subgroups and so on. But in such cases I think we typically need more investigation of how people respond, not less.
All that said, I certainly think that we should be careful not to over-optimise any single dimension, but instead carefully weigh all the relevant factors.
1. ^
  Though note that these are not arguments that we should assume that other considerations don’t matter. We should still assess each case on its merits and weigh all the considerations directly.

Framing EA: ‘Doing Good Better’ Did Worse

Rethink Priorities27 Oct 2025 15:06 UTC

162 points

14 comments4 min readEA link

David_Moss 24 Oct 2025 19:34 UTC
7 points
0 ∶ 0
in reply to: Jakob Lohmar’s comment on: Doing Prioritization Better
Thanks for your comment Jakob! A few thoughts:
- I think if we individuated “causes” in more fine-grained way, e.g. “Animal Welfare” → “Plant-based meat alternatives”, “Corporate Campaigns” etc., this might not actually change our analysis that much. Why? Prima facie, there are some more people who are working on questions like PBMA vs corporate campaigns, who would otherwise be counted as within-cause prioritisation in our current framework. But, crucially, these researchers are still only making prioritisations within the super-ordinate Animal Welfare cause. They’re not comparing e.g. PBMA to nuclear security initiatives. So I think you would need to say something: like these people are engaged in cause-level but within-cause prioritisation. This is technically a kind of (sub-)cause level prioritisation, but it lacks the cross-cause comparison that our CP and CCP has due to still being constrained within a single cause.
- The other thing that I’d note is that we also draw attention to the characteristic styles, and strengths and weaknesses, of cause prioritisation and intervention-level prioritisation. So, we argue, cause prioritisation is characterised more by abstract consideration of general features of the cause, whereas intervention-level prioritisation can increasingly attend to, more closely evaluate and potentially empirically study the specific details of the particular intervention in question. For example, it’s not possible to do a meaningful cost-effectiveness analysis of ‘Animals’ writ large,^[1] but it is possible to do so for a particular animal intervention. I would speculate that as you individuated causes in an increasingly fine-grained way, then their evaluation and prioritisation might become more intervention-like and less cause-like, as their evaluation becomes more tightly defined and more empirically tractable. My guess though is that a lot of even these more fine-grained sub-causes, might still be much more like causes than interventions in our analysis, insofar as they will still contain heterogeneous groups of interventions and so need to be evaluated more in terms of general characteristics of the set.
- I agree that if you individuated cause areas in an increasingly fine-grained way, so that each “cause” under consideration was an intervention (e.g. malaria nets in Uganda) or even a specific charity, then the cause/intervention distinction would collapse, in practice.
1. ^
  Although you could do so for the best single intervention within the cause.

David_Moss 19 Oct 2025 10:33 UTC
10 points
3 ∶ 0
on: Are longtermist ideas getting harder to find?
An alternative hypothesis is that less time is being devoted to these kinds of questions (see here and here).
This potentially has somewhat complex effects, i.e. it’s not just that you get fewer novel insights with 100 hours spent thinking than 200 hours spent thinking, but that you get more novel insights from 100 hours spent thinking when doing so against a backdrop of lots of other people thinking and generating ideas in an active intellectual culture.
To be clear, I don’t think this totally explains the observation. I also think that it’s true, to some extent, that the lowest hanging fruit has been picked, and that this kind of volume probably isn’t optimising for weird new ideas.
Perhaps related to the second point, I also think it may be the case that relatively more recent work in this area has been ‘paradigmatic’ rather than ‘pre-paradigmatic’ or ‘crisis stage’, which likely generates fewer exciting new insights.

[Question] What are the key uncertainties that are well-suited to a parliamentary approach?

David_Moss16 Oct 2025 20:53 UTC

6 points

0 comments1 min readEA link

David_Moss 14 Oct 2025 10:31 UTC
4 points
0 ∶ 0
on: Survey reveals chasm between public and expert views of AI bio-risk
A striking finding is that the area where people expect the greatest positive impact from AI is biosecurity and pandemic prevention
It seems like this might simply be explained by “biosecurity and pandemic prevention” containing two very different things: ‘novel biosecurity risks’ (of the kind EAs are concerned about) and ‘helping with the next covid-19’ (likely more salient to the general public and potentially involving broader healthcare improvements, which AI was also predicted to improve to a similar extent).
Perhaps relatedly, biosecurity and pandemic prevention was rated as the least a problem today (below everything other than AI itself).

David_Moss 10 Oct 2025 13:21 UTC
15 points
12 ∶ 2
on: Effective altruism in the age of AGI
Post-FTX, I think core EA adopted a “PR mentality” that (i) has been a failure on its own terms and (ii) is corrosive to EA’s soul.
I find it helpful to distinguish two things, one which I think EA is doing too much of and one which EA is doing too little of:
- Suppressing (the discussion of) certain ideas (e.g. concern for animals of uncertain sentience): I agree this seems deeply corrosive (even if an individual could theoretically hold onto the fact that x matters and even act to advance the cause of x, while not talking publicly about it, obviously the collective second-order effects mean that not publicly discussing x prevents many other people forming true beliefs about or acting in service of x (often with many other downstream effects on their beliefs and actions regarding y, z...).
- Attending carefully to the effect of communicating ideas in different ways: how an idea is communicated can make a big difference to how it is understood and received (even if all the expressions of the idea are equally accurate). For example, if you talk about “extinction from AI”, will people even understand this to refer to extinction and not the metaphorical extinction of job losses, or per your recent useful example, if you talk about “AI Safety”, will people understand this to refer to mean “stop all AI development”. I think this kind of focus on clear and compelling communication is typically not corrosive, but often neglected by EAs (and often undertaken only at the level of intuitive vibes, rather than testing how people receive communications differently framed.

David_Moss 10 Oct 2025 12:56 UTC
17 points
5 ∶ 0
on: Effective altruism in the age of AGI
Currently, the online EA ecosystem doesn’t feel like a place full of exciting new ideas, in a way that’s attractive to smart and ambitious people
This may be partly related to the fact that EA is doing relatively little cause and cross-cause prioritisation these days (though, since we posted this, GPI has wound down and Forethought has spun up).
People may still be doing within-cause, intervention-level prioritisation (which is important), but this may be unlikely to generate new, exciting ideas, since it assumes causes, and works only within them, is often narrow and technical (e.g. comparing slaughter methods), and is often fundamentally unsystematic or inaccessible (e.g. how do I, a grantmaker, feel about these founders?).
What links here?
- David_Moss's comment on Are longtermist ideas getting harder to find? by OscarD🔸 (19 Oct 2025 10:33 UTC; 10 points)

David_Moss 26 Sep 2025 18:41 UTC
10 points
0 ∶ 0
on: Evaluating the effectiveness of outreach within the EA movement
Thanks for the post! It’s great to see analysis of the LEAF data and engagement with existing EA Survey data.
much of the current research suggests these events [conferences, local groups, and educational programs] to be largely ineffective in encouraging participants to engage further with EA communities
That is not my impression of the existing data.
For example, you cite the 2019 cause prioritization report to say that:
Rethink Priorities’ analysis of the 2019 EA Survey found that 42% of respondents reported changing their primary cause area after becoming involved with an EA community. However, relatively few respondents had actually made career or behavioural changes to align with EA priorities.
I’m afraid I don’t understand the reason why you think this post suggests that claim. That post addressed cause prioritization, not behavioural changes, and I don’t think whether people changed their cause prioritization since joining EA is a good proxy for them making changes to align with EA priorities. Most respondents already supported EA causes at the time of joining EA (though many switch between causes or change their relative prioritizations over time).
In the report on Engagement from that same year, we find that large numbers of EAs are taking actions aligned with EA priorities (e.g. making EA donations, changing their career plans, volunteering or working in EA jobs, etc.).
a 2023 study of EAGx conferences, which compared the attitudes and behaviours of attendees with non-attendees, found no statistically significant differences between the two groups
I couldn’t find a post with the title you gave, but perhaps you are referring to this one? While I was very glad that they did the study, as I commented at the time, it was extremely under-powered, so finding non-significant effects was not surprising.
Participants’ responses were tracked before and after the Leaf 2025 course to evaluate belief changes. Overall, the dataset revealed very little net change in views towards the statement ‘we should prioritise what is evidenced as best over what we emotionally prefer’.
I’ve not dug into the LEAF data in detail (and thank you again for analyzing it). But it looks like the main reason why there was very little increase in people’s agreement with this statement was because respondents overwhelmingly agreed with it even in the pre condition. Mean ratings were 6.05 out of 7 at the start of the course, leaving almost no room for the score to go up.

David_Moss 26 Sep 2025 12:01 UTC
14 points
0 ∶ 0
on: 15 Easy, Low-Effort Ways to Support Your EA Group
Events like EAGx are rising in influence (15% of respondents now cite them as important in their EA journey), pushing conferences, meetups, social or other events is a high-leverage way to connect new people to the community.
As EA Survey from 2024 suggests, personal connections are one of the strongest channels through which people first hear about EA (17.9%) and go on to get involved (45%) — so your invites & referrals really move the needle and act in the similar way.
I agree. I would also add that personal contacts and EAGx are commonly cited as the largest positive influences on people’s ability to have an impact: personal contact with EAs is the most commonly cited (42.3% of respondents), while EAGx is cited by 13.1% of respondents (which should be interpreted in light of the fact that only minority of EAs have ever attended an EAGx). These factors are both particularly influential for the most highly engaged EAs.
They are also both highly close to the top most commonly mentioned sources of people making interesting and valuable new connections (EAG/EAGx combined is top (31.6%), followed by personal contacts (30.8%), with EAGx specifically being 19.2% of respondents.