Across loads of EA project, career development services and organisations in general there's a strong sentiment towards focusing on 'top talent'. For example in AI safety there are a few very well funded but extremely competitive programmes for graduates who want to do research in the field. Naturally their output is then limited to relatively small groups of people. An opposing trend seems to have gained traction in AI capability research as e.g. the "We have no moat" paper argued, where a load of output comes from the sheer mass of people working on the problem with a breadth-first approach. A corresponding opposite strategy for EA funds and career development services could be to spread the limited ressouces they have over a larger amount of people.
This concentration of funds on the development on a small group of top talent rather than distributing it over a wider group of people seems to me is a general sentiment quite prominent in the US economy and much less so in EU-countries like Germany, Scandinavia, the netherlands etc. I could imagine that EA origins in US/UK are a major reason for this structural focus.
Has anyone pointers to research on effectiveness comparisons between focusing on top talent vs a broader set of people, ideally in the context of EA? Or any personal thoughts/anecdotes to share on this?
Can you give more details what "distributing resources over a wider group of people" means for you? Are you arguing that mentors should spend much less time per person and instead mentor 3 times as many people? Are you arguing that researchers should get half as much money so twice as many researchers can get funded?
A plausible hypothesis is that ordinary methods of distributing resources over a wider group of people don't unlock that many additional researchers. Then, if there is only infrastructure that can support a limited number of people, then it is not very surprising to me that there is a focus on so-called 'top talent'. All else being equal, you would rather have competent people. And there is probably not some central EA decision that favors a small number of researchers over a large number of researchers.
Some side remark:
Naming the specific programmes might give you better answers here. People who want to answer have to speculate less, and if you are lucky the organizers of specific orgs might be inclined to answer.
They have much more resources than us.
Yes indeed that's what I am suggesting: if a strong bottleneck is mentoring for an org, one approach of "more broadly distributing ressources" might be that programmes increase their student-staff ratio (meaning a bit more self-guided work for each participant but more participants in total)
Prominent and very competitive programmes I was thinking of are SERI MATS and MLAB from redwood, but I think that extreme applicants-participant ratios are true for pretty much all paid and even many non-paid EA fellowships, e.g. PIBBSS or . Thanks for the hint that it ... (read more)