1. With regards to comparative advantages vs current grantmakers, I’ve been recently been thinking that it doesn’t seem *that* hard to beat them on dedication per dollar spent. Sure, someone like Luke Muehlhauser probably has better judgment and deeper expertise than me, but I can research something specific for much longer.
2. This kind of proposal could also take some degree of active grantmaking. I’m thinking mostly of soliciting proposals through prizes and then finding people for the most promising proposals, but there could be other approaches.
3. I’ve been thinking about how ALLFED relates to this. In some ways, it’s similar to what one would be aiming for, in terms of xrisk reduction per dollar, But they also did their own cost-effectiveness estimates in house, which led to some funders not liking them as much because their estimates were somewhat exaggerated/biased upwards, which is probably hard to avoid when one is very passionate about something.
4. I’d be particularly excited to see the part when one develops in-house x-risk reduction estimation capabilities. It seems like it could be useful for essentially any step in the funding pipeline, not just the beginning, though. A pretty natural thought is to increase the depth and expense of the quantification as the funding amounts go up, so it’s not clear that one should frontload the quantification at the beginning.
5. I thought that the “pointing people at a pretty clear target” and the “you are still getting the optimizer’s curse when evaluating stuff verbally, but you just don’t notice as much” were strong points.
1. With regards to comparative advantages vs current grantmakers, I’ve been recently been thinking that it doesn’t seem *that* hard to beat them on dedication per dollar spent. Sure, someone like Luke Muehlhauser probably has better judgment and deeper expertise than me, but I can research something specific for much longer.
2. This kind of proposal could also take some degree of active grantmaking. I’m thinking mostly of soliciting proposals through prizes and then finding people for the most promising proposals, but there could be other approaches.
3. I’ve been thinking about how ALLFED relates to this. In some ways, it’s similar to what one would be aiming for, in terms of xrisk reduction per dollar, But they also did their own cost-effectiveness estimates in house, which led to some funders not liking them as much because their estimates were somewhat exaggerated/biased upwards, which is probably hard to avoid when one is very passionate about something.
4. I’d be particularly excited to see the part when one develops in-house x-risk reduction estimation capabilities. It seems like it could be useful for essentially any step in the funding pipeline, not just the beginning, though. A pretty natural thought is to increase the depth and expense of the quantification as the funding amounts go up, so it’s not clear that one should frontload the quantification at the beginning.
5. I thought that the “pointing people at a pretty clear target” and the “you are still getting the optimizer’s curse when evaluating stuff verbally, but you just don’t notice as much” were strong points.