Curious what you're referring to here and if there's any publicly available information about it? Couldn't find anything in ALLFEDs 2020 and 2021 updates. (I'm trying to estimate the cost-effectiveness of this kind of project as part of my work at Rethink Priorities)
Another failure mode I couldn’t easily fit into the taxonomy that might warrant a new category:
Competency failures - EAs are just ineffective at achieving things in the world due to lack of skills (eg comms, politics, org running) or bad judgement. Maybe this could be classed as a resource failure (for failing to attract people with certain skills) or a rigor failure (for failing to develop them/learn from others). Will try to think of a title beginning with R…
Minor points:
Curious what people think of the argument that, given that people in the EA community have different rankings of the top causes, a close-to-optimal community outcome could be reached if individuals argmax using their own ranking?
(At least assuming that the number of people who rank a certain cause as the top one is proportional to how likely it is to be the top one.)
[Shortform version of this comment here.]
Update: I helped Linch collect data on the undergrad degrees of exceptionally successful people (using some of the ex post metrics Linch mentioned).
Of the 32 Turing Award winners in the last 20 years, 6 attended a top 10 US university, 16 attended another US university, 3 attended Oxbridge, and 7 attended other non-US universities. (full data)
Of the 97 Decacorn company founders I could find education data for, 19 attended a top 10 US university, 32 attended another US university, and 46 attended non-US universities (no Oxbridge). (full data)
So it seems like people who are successful on these metrics are pretty spread out across both US/elsewhere and elite/non-elite unis, but concentrated enough that having considerable focus on top US universities makes sense (assuming a key aim is to target people with the potential to be extremely successful).
The concentration gets a bit higher for PhDs for the Turing Award winners (28% at top 10 US universities). It’s also higher for younger Decacorn company founders (e.g., 50% of under-35s in the US at MIT or Stanford) – so that gives some (relatively weak) evidence that concentration at top US universities has increased in the last few decades.
There’s a doc with more details here for anyone interested.
Tl;dr: Most Turing Award winners and Decacorn company founders (i.e., exceptionally successful people) don’t attend US top universities, but there’s a fair amount of concentration.
In response to the post Most Ivy-smart students aren't at Ivy-tier schools and as a follow-up to Linch’s comment tallying the educational background of Field Medalists, I collected some data on the undergrad degrees of exceptionally successful people (using some of the (imperfect) ex post metrics suggested by Linch).
Of the 32 Turing Award winners in the last 20 years, 6 attended a top 10 US university, 16 attended another US university, 3 attended Oxbridge, and 7 attended other non-US universities. (full data)
Of the 97 Decacorn company founders I could find education data for, 19 attended a top 10 US university, 32 attended another US university, and 46 attended non-US universities (no Oxbridge). (full data)
So it seems like people who are successful on these metrics are pretty spread out across both US/elsewhere and elite/non-elite unis, but concentrated enough that having considerable focus on top US universities makes sense (assuming a key aim is to target people with the potential to be extremely successful).
The concentration gets a bit higher for PhDs for the Turing Award winners (28% at top 10 US universities). It’s also higher for younger Decacorn company founders (e.g., 50% of under-35s in the US at MIT or Stanford) – so that gives some (relatively weak) evidence that concentration at top US universities has increased in the last few decades.
There’s a doc with more details here for anyone interested.
[Also for full disclosure: I collected this data as part of my job, not just as a fun after hours project.]
Thought-provoking post, thanks a lot for writing it!
I broadly agree that it’s good for community builders to spend significant time on learning/direct work, especially if their long-term plan is not to do community building, but I think I disagree with some of your specific reasons.
I think the post sometimes conflates two senses of marketing. One is “pure” marketing, the other is marketing as you define it (i.e., marketing and ops), which includes things like organising content-heavy events and programs like fellowships. My instinct is that:
A. Most of the negative effects of “too much marketing” that you identify are negative effects of “pure” marketing, rather than marketing-and-operations. I think this is especially true of claim 2 and 4: It doesn’t seem to me like organising a talk or fellowship creates bad epistemics or makes EA comes across as pushy or single-minded. It’s maybe not always the best thing organisers could be doing (e.g., because of claim 1 and 3), but doesn’t seem harmful otherwise.
B. It’s not true that 60% of community builders spend 70-80% of their time on “pure” marketing.
I’m curious if you disagree with either of these claims. (But even if not, I think the central argument could still be true, though for slightly different reasons, e.g., that organisers spend too much time on “pure” marketing, or that spending significant time on learning/direct work makes you a better community builder.)
No worries!
I don’t have strong opinions on a 4-week fellowship, no! I think my quick take would be that (a) it’s harder to teach the core EA ideas well in 4x1.5h sessions, (b) it’s harder to create a social community/have people become friends in 4 weeks, and (c) the group of people who’d commit to a 4-week program but not an 8-week program is relatively small, at least in a university group context. But I’m not too sure about this. It also seems plausible to me that 4 weeks could be better in contexts like professional or city groups.
I’d be excited to see a group running both and comparing the outcomes (e.g., in terms of retention, later engagement, number of friends made, whether participants say they’d like a shorter/longer program).
Thanks for writing this post! I especially like the concrete alternatives with thoughtful upsides/downsides. As some others have said, I’d guess some of the downsides to the alternatives are quite significant, but would still love to see trials and to chat to anyone who runs trials.
A potentially useful alternative approach (especially for larger groups who can run multiple programs) is to have several alternative intro funnels at once. I.e. run the IF but also have a clear alternative for keen people with more background knowledge or who can quickly get background knowledge on their own, e.g. a retreat, a workshop or shorter version of the fellowship, mentorship, or something else. Organisers could scout for keen people both outside of the fellowship and in the first weeks. This might help preserve the benefits of the IF for those who need the accountability/long-term commitment, while allowing people who find it frustrating to skip through. A key uncertainty is how easy it is to identify keen people. If it’s difficult, it might be worth just running the program that benefits keen people the most (though I’m unsure about that).
Thanks for raising these points! A few of my (personal) reactions:
1. We definitely didn't intend for the post to presuppose that democracy is good for the long term. It’s true that most of the potential effects we identity are positive-leaning – but none of these effects, nor the all-things-considered effect, is a settled case.
2. I think the question of what conditions allowed EA to come into existence is interesting, although not sure if that's the main positive impact of liberal democracy (especially given we don’t have super strong evidence that liberal democracy was necessary for EA to arise). As is sort-of mentioned in the post, (inclusive) liberalism might be the feature most directly important to the flourishing of EA. But of course it’s hard to tell and I think it’s plausible that a combination of features reinforcing each other is key.
Thank you for the important post!
My naive prediction would be that many other factors predicting information-processing capacity (e.g., number of connections, conduction velocity, and refractory period) are positively correlated with neuron count, such that neuron count is pretty strongly correlated with information processing even if it only plays a minor part in causing more information processing to happen.
You cite one paper (Chitka 2009) that provides some evidence against my prediction (based on skimming the abstract, this seemed to be roughly by arguing that insect brains are not necessarily worse at information processing than vertebrate brains). Curious if you think this is the general trend of the literature on this topic?