In most cases so far, the counterfactual is little research, rather than using some other consultancy. And in the wider landscape, there seems to be just very little in the direction of what we’d call EA charity recommendations. There’s GiveWell / Open Phil, there’s philanthropic advising that’s very heavily about understanding the preferences of the donor and finding charities that ‘fit’ those preferences, and there seems to us to be a very significant gap in the middle.
Seems pretty convincing. This work also seems somewhat well suited to CEA, since you’re a natural point of contact for people interested in giving better, and large donors will be more impressed by recommendations made by an Oxford-affiliated organization.
If that means we should abandon policy and politics as a whole, however, I think that would be wrong. Politics is a huge lever in the world, perhaps the single biggest lever, and to dismiss from the outset that whole method of making the world better would be to far too quickly narrow down our options.
I agree that it seems like a big important lever, but I’m less certain that it’s a good fit for the profile of strengths the EA movement has currently built up. If someone was to create an app that made running ideological turing tests easy, and EAs in charge of policymaking were passing them at a much higher rate than matched controls with comparable education and ability, that’s the kind of thing that might convince me that policy was a comparative advantage. (Same for winning bets about the results of particular policies with matched controls.) So far, I’ve seen much more focus on e.g. creating people with high earning careers than creating people who score well according to these criteria. (Although that’s not the only conceivable approach—one could imagine the EA movement pushing for the legalization of prediction markets to outsource the work of making accurate predictions, for instance.)
Seems pretty convincing. This work also seems somewhat well suited to CEA, since you’re a natural point of contact for people interested in giving better, and large donors will be more impressed by recommendations made by an Oxford-affiliated organization.
I agree that it seems like a big important lever, but I’m less certain that it’s a good fit for the profile of strengths the EA movement has currently built up. If someone was to create an app that made running ideological turing tests easy, and EAs in charge of policymaking were passing them at a much higher rate than matched controls with comparable education and ability, that’s the kind of thing that might convince me that policy was a comparative advantage. (Same for winning bets about the results of particular policies with matched controls.) So far, I’ve seen much more focus on e.g. creating people with high earning careers than creating people who score well according to these criteria. (Although that’s not the only conceivable approach—one could imagine the EA movement pushing for the legalization of prediction markets to outsource the work of making accurate predictions, for instance.)