David_Moss

An­nounc­ing EA Sur­vey 2022

How many peo­ple have heard of effec­tive al­tru­ism?

An­nounc­ing EA Pulse, large monthly US sur­veys on EA

Up­dates on Com­mu­nity Health Sur­vey Results

Are 1-in-5 Amer­i­cans fa­mil­iar with EA?

Why some peo­ple dis­agree with the CAIS state­ment on AI

EA Sur­vey 2022: Demographics

• David_Moss 1 Apr 2024 11:28 UTC

  112 points

  16 ∶ 0

  on: EA is now scan­dal-constrained

  Our data suggests that the highest impact scandals are several times more impactful than other scandals (bear in mind that this data is probably not capturing the large number of smaller scandals).

  

  If so, it seems plausible we should optimise for the very largest scandals, rather than simply producing a large volume of less impactful scandals.

EA Sur­vey 2019 Series: How EAs Get In­volved in EA

EA Sur­vey 2020: Demographics

• David_Moss 10 Sep 2023 18:02 UTC

  106 points

  25 ∶ 9

  on: Thoughts on EA, post-FTX

  Still, it’s hard to see how tweaking EA can lead to a product that we and others be excited about growing.

  It’s not clear to me how far this is the case.

  • Re. the EA community: evidence from our community survey, run with CEA, suggests a relatively limited reduction in morale post-FTX.

  • Re. non-EA audiences, our work reported here and here (though still unpublished due to lack of capacity) suggest relatively low negative effects in the broader population (including among elite US students specifically).

  I agree that:

  • Selection bias (from EAs with more negative reactions dropping out) could mean that the true effects are more negative.

    • I agree that if we knew large numbers of people were leaving EA this would be another useful datapoint, though I’ve not seen much evidence of this myself. Formally surveying the community to see how many people know of leaving could be useful to adjudicate this.

    • We could also conduct a ‘non-EA Survey’ which tries to reach people who have dropped out of EA, or who would be in EA’s target audience but who declined to join EA (most likely via referrals), which would be more systematic than anecdotal evidence. RP discussed doing with with researchers/​community builders at another org, but haven’t run this due to lack of capacity/​lack of funding.

  • If many engaged EAs are dropping out but growth is continuing only because “new recruits are young and naive about EA’s failings,” this is bad.

    • That said, I see little reason to think this is the case.

    • In addition, EA’s recent growth rates seem higher than I would expect if we were seeing considerable dropout.

  Especially considering that we have the excellent option of just talking directly about the issues that matter to us, and doing field-building around those ideas—AI safety, Global Priorities Research, etc. and so on. This would be a relatively clean slate, allowing us to do more (as outlined in 11), to discourage RB, and stop bad actors.

  It’s pretty unclear to me that we would expect these alternatives to do better.

  One major factor is that it’s not clear that these particular ideas/​fields are in a reputationally better position than EA. Longtermist work may have been equally or more burned by FTX than EA. AI safety and other existential risk work have their own reputational vulnerabilities. And newer ideas/​fields like ‘Global Priorities Research’ could suffer from being seen as essentially a rebrand of EA, especially if they share many of the same key figures/​funding sources/​topics of concern, which (per your 11a) risks being seen as deceptive. Empirical work to assess these questions seems quite tractable and neglected.

  Re. your 10f-g, I’m less sanguine that the effects of a ‘reset’ of our culture/​practices would be net positive. It seems like it may be harder to maintain a good culture across multiple fragmented fields in general. Moreover, as suggested by Arden’s point number 1 here, there are some reasons to think that basing work solely around a specific cause may engender a less good culture than EA, given EA’s overt focus on promoting certain virtues.

  What links here?

  • How has FTX’s col­lapse im­pacted EA? by AnonymousEAForumAccount (17 Oct 2023 17:02 UTC; 239 points)
  • JWS's comment on Thoughts on EA, post-FTX by RyanCarey (15 Sep 2023 17:42 UTC; 11 points)

EA Sur­vey 2020: Cause Prioritization

EA Sur­vey 2020: How Peo­ple Get In­volved in EA

EA Sur­vey 2019 Series: Com­mu­nity Information

An­nounc­ing Sur­veys on Com­mu­nity Health, Causes, and Harassment

EA Sur­vey 2018 Series: Dona­tion Data

EA Sur­vey 2019 Series: How many peo­ple are there in the EA com­mu­nity?

EA Sur­vey 2018 Series: Cause Selection

EA Groups Sur­vey 2020

• David_Moss 25 Sep 2020 9:26 UTC

  55 points

  0 ∶ 0

  on: Cor­re­la­tions Between Cause Pri­ori­ti­za­tion and the Big Five Per­son­al­ity Traits

  Thanks a lot for looking at this! I’m also fascinated by possible links between Big 5 and other personality/​psychometric measures, and EA related judgements, and think this kind of analysis could be quite informative about EA thinking, and perhaps prioritisation in particular. To echo another commenter, I also like the graphs.

  Unfortunately, we had to drop all of our psychometric measures last year due to space constraints, but I hope that we may be able to reintroduce them at some point.

  I recall that when I looked into possible relationships between our Big 5 measures and cause prioritisation, treating the response categories as an ordinal scale, and found mostly null results. One reason might have been low reliability of some of the measures: we used an established short form measure of the Big 5, the Ten Item Personality Inventory, which often seems to face low reliability issues.

  It’s interesting that you found such strong results looking at the difference between people who indicated that the cause should receive no resourcess versus those who indicated that it is the top priority. One thing worth bearing in mind is that these are very small proportions of the responses overall. Unfortunately the Forum now formats our 2018 post weirdly, with all the images really small, but you can see the distribution here:

  

  It seems possible to me that ‘extreme responders’ indicating that a cause should receive no resources vs or it’s the top priority might be a slightly unusual group overall (a priori, I might have expected ‘no resources’ respondents to be less agreeable and less conscientious). The results might also be influenced a little by the minority of respondents who selected multiple causes as “top cause”, since these would disproportionately appear in your ‘top cause’ category.

  It also seems likely that there might be confounders due to demographic differences which are associated with differences in Big 5. For example, there are big gender differences, which vary across the lifespan (see here), i.e. women are higher in Conscientiousness, Agreeableness, Openness, and Extraversion, although this varies at the aspect level (you can see the age x gender population norms for the TIPI specifically here and here), and we know that there were dramatic gender differences in cause prioritisation.

  For example, women were much more supportive of Climate Change than men in our survey, so if women are more Conscientious, this would plausibly show up as a difference in Conscientiousness scores between supporters and opponents of Climate Change as a cause. So presumably you’d want to control for other differences in order to determine whether the difference in personality traits seems to predict the difference in cause prioritisation. Of course there could be other differences which are relevant, for example, I seem to recall that I found differences in the personality traits of LessWrong members vs non-LessWrong members (which could also be confounded by gender).