I’ve thought about this on-and-off over the last 3 months, and my current tentative conclusion is that the succinct version of my comment (“research orgs can be mega-projects”) is obviously true and the strong version of the OP is wrong.
In addition to the examples above (19 US universities with budgets >1B/year, existence of large foundations), we can also look at the most recent post about RTI, with a budget of nearly a billion. You can also look at a number of thinktanks, the past budget of Bell Labs, or the R&D departments of major corporations.
I think a more sophisticated objection (which I suspect Khorton doesn’t believe) is that you just can’t make a research org that big without most of it being subsumed by fake work with low moral import, see e.g. RTI, the other recent EAF post about Fraunhofer, academic research universities, etc.
(I also don’t really believe the more sophisticated objection myself, because as an empirical matter humans do appear to be making progress on scientific matters, and I think a lot of said progress is made within large institutions?)
Concretely, I think both RP and Open Phil have a decent shot* of scaling up to >100M/year without substantial loss of rigor, mission creep, etc, though it might take many years and may not be worth it. I also believe this about Redwood Research, and (to a lesser extent) FHI if they decide to shed off the Oxford mantle.
*to be clear I’m not saying that this will happen by default, nor that it’s necessarily advisable. Scaling is never easy, and it’s certainly harder in the nonprofit world than in startups due to aspects like the lack of contact with reality, it being easier to do fake work, etc.
I think EA orgs are relevantly different from most non-EA orgs, in that EA orgs often desire staff that have a detailed understanding of EA thinking—which few people have. By contrast, you typically don’t need anything analogous to work at the Bill and Melinda Gates Foundation or at a university. That’s a reason to believe it’s harder to scale EA research orgs quickly.
I think that is a reason that we can’t quickly scale, but not a strong reason that we can’t eventually reach a similar scale to Gates/universities.
I expect that as these fields mature, we’ll break things down into better-defined problems that can be more effectively done by less aligned people. (I think this is already happening to some extent—e.g. compare the type of AI timelines research needed 5 years ago vs. asking someone to do more research into the parameters of recent OP reports.)
From the outside, Givewell work also feels much more regimented and doable by less-aligned people, compared to the early heady days when Holden and Elie were hacking things out from first principles without even knowing about QALYs.
Potentially, but I think the debate largely concerned near-term megaprojects. Cf.:
people able to run big EA projects seem like one of our key bottlenecks right now … I’m especially excited about finding people who could run $100m+ per year ‘megaprojects’
And to the extent that we’re discussing near-term megaprojects, quick scaling matters.
RTI and the Bill and Melinda Gates Foundation in your earlier comment are good counterexamples to what I said—I didn’t expect to see a research organisation hiring quite that many people. I would be really surprised to see the organisations you listed grow to more than 5000 employees, but you’re right that it’s not impossible, especially for Open Philanthropy.
I don’t think of Bell Labs as a counterexample because afaik they spent a lot of money on expensive equipment, rather than spending $50M+ just on staff, but maybe I’m wrong about that.
Note that at $100M/year, having >5000 employees means the average cost per employee is <20k people.
Also I think Ben’s post about scalability was primarily about cost-effective ways to deploy capital at scale, so number of employees isn’t a major crux.
I’ve thought about this on-and-off over the last 3 months, and my current tentative conclusion is that the succinct version of my comment (“research orgs can be mega-projects”) is obviously true and the strong version of the OP is wrong.
In addition to the examples above (19 US universities with budgets >1B/year, existence of large foundations), we can also look at the most recent post about RTI, with a budget of nearly a billion. You can also look at a number of thinktanks, the past budget of Bell Labs, or the R&D departments of major corporations.
I think a more sophisticated objection (which I suspect Khorton doesn’t believe) is that you just can’t make a research org that big without most of it being subsumed by fake work with low moral import, see e.g. RTI, the other recent EAF post about Fraunhofer, academic research universities, etc.
(I also don’t really believe the more sophisticated objection myself, because as an empirical matter humans do appear to be making progress on scientific matters, and I think a lot of said progress is made within large institutions?)
Concretely, I think both RP and Open Phil have a decent shot* of scaling up to >100M/year without substantial loss of rigor, mission creep, etc, though it might take many years and may not be worth it. I also believe this about Redwood Research, and (to a lesser extent) FHI if they decide to shed off the Oxford mantle.
*to be clear I’m not saying that this will happen by default, nor that it’s necessarily advisable. Scaling is never easy, and it’s certainly harder in the nonprofit world than in startups due to aspects like the lack of contact with reality, it being easier to do fake work, etc.
I think EA orgs are relevantly different from most non-EA orgs, in that EA orgs often desire staff that have a detailed understanding of EA thinking—which few people have. By contrast, you typically don’t need anything analogous to work at the Bill and Melinda Gates Foundation or at a university. That’s a reason to believe it’s harder to scale EA research orgs quickly.
I think that is a reason that we can’t quickly scale, but not a strong reason that we can’t eventually reach a similar scale to Gates/universities.
I expect that as these fields mature, we’ll break things down into better-defined problems that can be more effectively done by less aligned people. (I think this is already happening to some extent—e.g. compare the type of AI timelines research needed 5 years ago vs. asking someone to do more research into the parameters of recent OP reports.)
From the outside, Givewell work also feels much more regimented and doable by less-aligned people, compared to the early heady days when Holden and Elie were hacking things out from first principles without even knowing about QALYs.
Potentially, but I think the debate largely concerned near-term megaprojects. Cf.:
And to the extent that we’re discussing near-term megaprojects, quick scaling matters.
I see, I agree with that.
RTI and the Bill and Melinda Gates Foundation in your earlier comment are good counterexamples to what I said—I didn’t expect to see a research organisation hiring quite that many people. I would be really surprised to see the organisations you listed grow to more than 5000 employees, but you’re right that it’s not impossible, especially for Open Philanthropy.
I don’t think of Bell Labs as a counterexample because afaik they spent a lot of money on expensive equipment, rather than spending $50M+ just on staff, but maybe I’m wrong about that.
Note that at $100M/year, having >5000 employees means the average cost per employee is <20k people.
Also I think Ben’s post about scalability was primarily about cost-effective ways to deploy capital at scale, so number of employees isn’t a major crux.