David_Moss

Karma: 9,313

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 Apr 29, 2025, 1:37 PM
4 points
1 ∶ 0
in reply to: NickLaing’s comment on: Doing Prioritization Better
Thank you for the reply Nick.
I agree there’s the ethical commensurability factor, but I’m not talking about moral intuintions, or domain specific knowledge, but about concrete reality—even if that reality is unknown. I’m saying that cross-cause comparison increases objective (not subjective) uncertainty by orders of magnitude.
I think my remarks above apply across different kinds of uncertainty (we discuss ethical, empirical and other kinds of uncertainty above). That said, I’m not sure I follow your intended point about objective uncertainty (your example given seems to be about subjective uncertainty about moral weight), but it seems to me my remarks would apply exactly the same to objective uncertainty.
To put it another way, in many cases moral weight doesn’t matter for within cause comparison, but it becomes critically imporant between causes… this huge objective increase in uncertainty here is an important if fairly basic point to recognise.
We make the point (using the same examples) that comparisons across causes introduce many huge uncertainties, that do not apply within-causes, at multiple points in the passages quoted above and elsewhere. So I fear we may be talking past each other if you see this point as missing from the article.

David_Moss Apr 29, 2025, 9:25 AM
4 points
1 ∶ 0
in reply to: NickLaing’s comment on: Doing Prioritization Better
Thanks for the comment Nick.
The article discusses these difficulties, including the same specific example of cross-species comparisons here:
With that broad a mandate, however, come significant challenges. One of the biggest issues is ethical commensurability – essentially, how do you compare ‘good done’ across wildly different spheres? Each cause tends to have its own metrics and moral values, and these don’t easily line up. Saving a child’s life can be measured in DALYs or QALYs, but how do we directly compare that to reducing the probability of human extinction, or to sparing chickens from factory farms? Cross-cause analysis must somehow weigh very different outcomes against each other, forcing thorny value judgments. One concrete example is comparing global health vs. existential risk. Global health interventions are often evaluated by cost per DALY or life saved, whereas existential risk reduction is about lowering a tiny probability of a huge future catastrophe. A cross-cause perspective has to decide how many present-day lives saved is “equivalent” to a 0.01% reduction in extinction risk – a deeply fraught question. Likewise, comparing human-centric causes to animal-focused causes requires assumptions about the relative moral weight of animal suffering vs. human suffering. If there’s no agreed-upon exchange rate (and people’s intuitions differ), the comparisons can feel too disparate. Researchers have attempted to resolve this by creating unified metrics or moral weight estimates (for instance, projects to estimate how many shrimp-life improvements rival a human-life improvement), but there’s often no escaping the subjective choices involved. This means cross-cause prioritization can be especially contentious and uncertain: small changes in moral assumptions or estimates can flip the ranking of causes, leading to debate.
...
Aggregating evidence across causes is very hard – the data and methodology you use to assess a poverty program vs. an AI research project are entirely different. Having worked on broad cross-domain analyses of this kind, we have previously noted how difficult it is to incorporate “the vast number of relevant considerations and the full breadth of our uncertainties within a single model” when comparing across domains
We also discuss this in the context of cause prioritisation here. I think it’s important to note that these difficulties apply to any comparison across causes (not just intervention-level cross-cause prioritisation), and so can’t be dodged if you are interested in cause-neutrally identifying the best interventions.
However, in other ways, comparing the value of different causes can be especially challenging. Researchers must consider ethical trade-offs, uncertainty, and the potential for model errors. At its best, this means that cause prioritization can lead to the beneficial development of frameworks, metrics, and criteria that improve prioritization methods overall. At its worst, and sometimes more commonly, it just leads to lots of intuition-jousting between vague qualitative heuristics.
That said, I would encourage people to reflect carefully about their attitudes towards uncertainty before concluding that:
If we are uncertainty averse, then cross cause prioritisation becomes much less attractive.
Whether this makes sense will depend on your specific attitudes towards uncertainty, and the specific circumstances of the case.
Specific kinds of uncertainty aversion might lead a person to favour focusing their resource allocation only on interventions where they are highly certain about the effect of the intervention. If these interventions are concentrated within a single cause, this might lead them to focus their prioritisation within that cause. Or, they might focus their prioritisation within a given cause because this will allow them to maximise their certainty about outcomes (due to domain-specific knowledge, as we discuss elsewhere).
But it’s not clear that such a person should focus their prioritisation within a single cause. It may be that the interventions about which they can be most certain are not concentrated within one cause, but rather spread across different causes. If so, their search for highly certain interventions should potentially spread across causes.
It’s also worth noting explicitly the difference between uncertainty about interventions and uncertainty about comparisons between interventions. Our observations above show that the comparison of interventions in different causes may often be particularly uncertain (e.g. being uncertain about the relative weight of human and chicken suffering). But it seems very unclear what normatively follows from this. Note that if you are uncertain about how to compare A and B, just deciding to focus your efforts on one doesn’t reduce your uncertainty about the comparison at all. And deciding to focus your prioritisation effort on one just doubles-down on your ignorance, by electing to not conduct the prioritisation research that would resolve your uncertainty.
In addition, as we note elsewhere, concern about uncertainty could also push towards diversification, which likely recommends prioritisation across cause areas in order to identify less correlated interventions:
Concern over avoiding wasted efforts calls for diversifying resources across multiple causes to reduce the risk of correlated outcomes from overfocusing on one area. For instance, an organization might allocate funding across global health, AI, and biosecurity projects to ensure that a setback in one field does not derail all progress. Intervention and cause diversification, made possible through a blend of cause-level and cross-cause prioritization work, builds resilience and increases the probability of achieving impact.

David_Moss Apr 25, 2025, 10:49 AM
4 points
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on: 80,000 Hours is hiring for an Engagement Specialist
We’re also the largest single source of people getting involved in the effective altruism community, according to the most recent EA Survey.
Just to note that the even more recent EA Survey is here, and 80K are indeed still the single source most commonly cited as important for people getting involved!

David_Moss Apr 24, 2025, 9:43 AM
4 points
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in reply to: Vasco Grilo🔸’s comment on: EA Survey 2022: Geography
Thanks Vasco. Yes, there will be a similar post for EAS 2024. But if you need any specific results in the meantime we can easily provide those.

David_Moss Apr 15, 2025, 12:48 PM
2 points
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in reply to: James Herbert’s comment on: EA Survey 2024: What Helps People Have an Impact and Connect with Other EAs
If anyone reading this has a say in future surveys, for what it’s worth, I’d be keen to see this question included.
Thanks James! Yes, we’d encourage any readers to flag what questions they would find most useful.

David_Moss Apr 15, 2025, 10:12 AM
6 points
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in reply to: James Herbert’s comment on: EA Survey 2024: What Helps People Have an Impact and Connect with Other EAs
Thanks James!
We previously asked this question in 2019. The modal response was 0 such connections, followed by 1-2, though there was a long tail of >10 connection respondents. Connections were also far higher for highly engaged EAs (60.7% of highly engaged EAs had >10 connections, compared to 13.7% for considerably (4/5) engaged EAs, and <2% for anyone less engaged).
We cut the question due to lack of space and it not being prioritized by core orgs making requests of us. But we’d be happy to reintroduce if there is sufficient interest.

David_Moss Apr 3, 2025, 4:57 PM
12 points
1 ∶ 0
in reply to: Manuel Allgaier’s comment on: Centre for Effective Altruism Is No Longer “Effective Altruism”-Related
Maybe a slogan could be “All altruism is effective”?

David_Moss Apr 2, 2025, 10:49 AM
25 points
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on: Centre for Effective Altruism Is No Longer “Effective Altruism”-Related
RP actually did some empirical testing on this and we concluded that people really like the name “Effective Altruism”, but not the ideas, values or mission.
That’s unfortunate. But I think it suggests there’s scope for a new ‘Centre for Effective Altruism’ to push forward exciting new ideas that have more mainstream appeal, like raising awareness of the cause du jour, while the rebranded Center for ████████ continues to focus on all the unpopular stuff.

David_Moss Apr 2, 2025, 8:59 AM
9 points
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on: My “infohazards small working group” Signal Chat may have encountered minor leaks
I think it was a mistake to post about “Hidden Capabilities Evals Leaked In Advance to Bioterrorism Researchers and Leaders (minor)” in a public forum… it seems too minor! Maybe if you’d included some specific examples it would be more useful.

David_Moss Apr 1, 2025, 9:59 PM
2 points
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in reply to: Alex (Αλέξανδρος)’s comment on: Stewardship: CEA’s 2025-26 strategy to reach and raise EA’s ceiling
Thank you for the kind words about my input Alex! I should clarify for others though that Alex is being too generous. I’ve only commented on a draft of theirs, the project is all their work.

David_Moss Mar 27, 2025, 12:39 PM
2 points
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in reply to: LMKull’s comment on: EA Survey 2024: How People Get Involved in EA
Are introductory fellowships and other courses run by local EA groups considered under “educational courses” or does that mean things like philosophy classes, where EA might be mentioned as a concept?

There are two different things to consider here:
- People’s response to the main question about where they heard about EA, which was a selection from a fixed list. So this just means the respondent selected “Educational course (e.g., lecture, class, MOOC)”, with no additional classification from us.
- Their responses to the open comment follow-up question asking for more detail: the majority of these (>75%) refer to a university course or the Singer MOOC.
In most cases where someone joins EA through an activity run by their EA group, they’ll select EA Group. I went through references to “group” in the comments for those who did not select EA Group and most (23/36) were not referring to an EA Group, 3 referred to a friend referring them to a group, 2 referred to seeing an ad for a group, 5 mentioned something else first introducing them to EA but a group being useful for them beginning to seriously engage and the rest were miscellaneous/uncategorisable. I went through comments of those who did select EA Group and 9/111 (8%) mentioned a fellowship. You can see a more detailed analysis of comments by those who selected EA Group in 2020 here, where 7% mentioned a fellowship, but a larger number mentioned an event or fresher’s fair.
Alternatively, would it be possible to ask for country-specific data analysis?
For Estonia, there are not very clear differences (p=0.023). This is from n=37 for Estonia, so we should not be very confident about the differences.

David_Moss Mar 26, 2025, 2:21 PM
5 points
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in reply to: Benjamin M.’s comment on: EA Survey 2024: How People Get Involved in EA
Thanks for raising this interesting point!
If we look direction at the association between active outreach and levels of engagement, we see no strong relationship (aside from within the very small “No engagement with EA” category).
I agree that it’s intuitively plausible, as you say, that people who actively sought out EA might be expected to be more inclined to high engagement.
But I think that whether the person encounters EA through active outreach (influencing selection) may often be in tension with whether the person encounters EA through a high-touch form of engagement (leading to different probability of continued engagement). For example, EA Groups are quite active outreach (ex hypothesi, leading to lower selection for EA inclination), but higher touch (potentially leading to people being more likely to get engaged), whereas a book is more passive outreach (ex hypothesi, leading to higher selection for EA inclination), but lower touch (and so may be less likely to facilitate engagement)^[1].
1. ^
  There may be other differences between these particular two examples of course. For example, EA Groups and EA books might select in different ways.

David_Moss Mar 25, 2025, 8:36 PM
4 points
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in reply to: Ian Turner’s comment on: EA Survey 2024: How People Get Involved in EA
I definitely agree that this seems unusual (and our results show that it is!). Still, it seems reasonable that a very small number of people might stumble across an EAGx first, as in Arden’s anecdote below.

David_Moss Mar 25, 2025, 12:48 PM
6 points
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in reply to: David_Moss’s comment on: EA Survey 2024: How People Get Involved in EA
@titotal I’m curious whether or to what extent we substantively disagree, so I’d be interested in what specific numbers you’d anticipate, if you’d be interested in sharing.
- My guess is that we’ll most likely see <30% reduction in people first hearing about EA from 80K next time we run the survey (though this might be confounded if 80K don’t promote the EA Survey so much, so we’d need to control for that).
- Obviously we can’t directly observe this counterfactual, but I’d guess that if a form of outreach that was 100% active shut down, we’d observe close to a 100% reduction (e.g. if everyone stopped running EA Groups or EAGs, we’d soon see ~0% people hearing about EA from these sources).^[1]
1. ^
  I don’t say strictly 0% only because I think there’s always the possibility for a few unusual cases, e.g. someone is googling how to do good and happens across an old post about EAG or their inactive local group.

David_Moss Mar 24, 2025, 9:47 PM
8 points
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in reply to: titotal’s comment on: EA Survey 2024: How People Get Involved in EA
I’m imagining someone googling “ethical career” 2 years from now and finding 80k, noticing that almost every recent article, podcast, and promoted job is based around AI, and concluding that EA is just an AI thing now.
I definitely agree that would eventually become the case (eventually all the older non-AI articles will become out of date). I’m less sure it will be a big factor 2 years from now (though it depends on exactly how articles are arranged on the website and so how salient it is that the non-AI articles are old).
It could also be bad even for AI safety: There are plenty of people here who were initially skeptical of AI x-risk, but joined the movement because they liked the malaria nets stuff. Then over time and exposure they decided that the AI risk arguments made more sense than they initially thought, and started switching over.
I also think this is true in general (I don’t have a strong view about the net balance in the case of 80K’s outreach specifically).
Previous analyses we conducted suggested that over half of Longtermists (~60%) previously prioritised a different cause and that this is consistent across time.
You can see the overall self-reported flows (in 2019) here.

David_Moss Mar 24, 2025, 6:02 PM
5 points
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in reply to: Arden Koehler’s comment on: EA Survey 2024: How People Get Involved in EA
Thanks Arden!

I also agree that prima facie this strategic shift might seem worrying given that 80K has been the powerhouse of EA movement growth for many years.
That said, I share your view that growth via 80K might reduce less than one would naively expect. In addition to the reasons you give above, another consideration is our finding is that a large percentage of people get into EA via ‘passive’ outreach (e.g. someone googles “ethical career” and finds the 80K website’, and for 80K specifically about 50% of recruitment was ‘passive’), rather than active outreach, and it seems plausible that much of that could continue even after 80K’s strategic shift.
Our framings will probably change. It’s possible that the framings we use more going forward will emphasise EA style thinking a little less than our current ones, though this is something we’re actively unsure of.
As noted elsewhere, we plan to research this empirically. Fwiw, my guess is that broader EA messaging would be better (on average and when comparing the best messaging from each) at recruiting people to high levels of engagement in EA (this might differ when looking to recruit people directly into AI related roles), though with a lot of variance within both classes of message.

David_Moss Mar 21, 2025, 9:27 AM
7 points
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on: Informal Poll on Moral Realism Among EAs at EAG Bay Area
Thanks for posting!

We did ask about this in the 2015 and 2017 EA Surveys. We’ve not repeated it since then due to limited space.
In both cases, respondents were primarily realist (50.9% in 2015, 42.5% in 2017).

David_Moss Mar 17, 2025, 8:11 PM
6 points
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in reply to: OscarD🔸’s comment on: Existential Choices Symposium with Will MacAskill and other special guests (3-5pm GMT Monday)
A broader coalition of actors will be motivated to pursue extinction prevention than longtermist trajectory changes… For instance, see Scott Alexander on the benefits of extinction risk as a popular meme compared to longtermism.
This might vary between:
- The level of the abstract memes:
  - I agree “reducing risk of extinction (potentially in the near term)” may be more appealing than “longtermist trajectory change”
- The level of concrete interventions:
  - “Promoting democracy” (or whatever one decides promotes long term value) might be more appealing than “reducing risk from AI”^[1] (though there is likely significant variation within concrete interventions).
1. ^
  Though our initial work does not suggest this.

David_Moss Mar 14, 2025, 2:19 PM
48 points
5 ∶ 0
on: Where Are the Older People in Our Movement?
I agree this is a potential concern.
As it happens, since 2020, the community has continued to age. As of the end of last year, it’s median 31, mean 22.4, and we can see that it has steadily aged across years.
It’s clear that a key contributor to our age distribution is the age at which people first get involved with EA, which is median 24, mean 26.7, but the age at which people first get involved has also increased over time.
I think people sometimes point to our outreach focusing on things like university groups to explain this pattern. But I think this is likely over-stated, as this accounts for only a small minority of our recruiting, and most of the ways people first hear about EA seems to be more passive mechanisms, not tied to direct outreach, which would be accessible to people at older ages (we’ll discuss this in more detail in the 2024 iteration of this post).
That said, different age ranges do appear to have different levels of awareness of EA, with highest awareness seeming to be at the 25-34 or 35-44 age ranges. (Though our sample size is large, the number of people who we count as aware of EA are very low, so you can see these estimates are quite uncertain. Our confidence in these estimates will increase as we run more surveys). This suggests that awareness of EA may be reaching different groups unevenly, which could partly contribute to lower engagement from older age groups. But this need not be the result of differences in our outreach. It could result from different levels of interest from the different groups.

David_Moss Mar 12, 2025, 10:30 AM
9 points
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on: Winning is underrated in grassroots movements
Matthew Yglesias has written more critically about this tendency (which he thinks is widely followed in activist circles, but is often detrimental). For example, here he describes what he refers to as “activist chum”, which is good for motivating and fundraising (very important for the self-interest of (those leading) movement), but can lead to focusing on “wins” that aren’t meaningful and may be unhelpful.
The chum comes from the following political organizing playbook that is widely followed in progressive circles:
1. Always be asking for something.
2. Ask for something of someone empowered to give it to you.
3. Ask for something from someone who cares what you think.