There are no sharp cut offs—just gradually diminishing returns.
An org can pretty much always find a way to spend 1% more money and have a bit more impact. And even if an individual org appears to have a sharp cut off, we should really be thinking about the margin across the whole community, which will be smooth. Since the total donated per year is ~$400m, adding $1000 to that will be about equally as effective as the last $1000 donated.
You seem to be suggesting that Open Phil might be overfunding orgs so that their marginal dollars are not actually effective.
But Open Phil believes it can spend marginal dollars at ~7x GiveDirectly.
I think what’s happening is that Open Phil is taking up opportunities down to ~7x GiveDirectly, and so if small donors top up those orgs, those extra donations will be basically as effective as 7x GiveDirectly (in practice negligibly lower).
There are no sharp cut offs—just gradually diminishing returns.
An org can pretty much always find a way to spend 1% more money and have a bit more impact.
The marginal impact can be much smaller, but this depends on the particulars. I think hiring is the most important example, especially in cases where salaries make up almost all of the costs of the organization. Suppose a research organization hired everyone they thought was worth hiring at all (with their current management capacity as a barrier, or based on producing more than they cost managers, or based on whether they will set the org in a worse direction, etc.). Or, the difference between their last hire and their next hire could also be large. How would they spend an extra 1% similarly cost-effectively? I think you should expect a big drop in marginal cost-effectiveness here.
Maybe in many cases there are part-time workers you can get more hours from by paying them more.
And even if an individual org appears to have a sharp cut off, we should really be thinking about the margin across the whole community, which will be smooth. Since the total donated per year is ~$400m, adding $1000 to that will be about equally as effective as the last $1000 donated.
I think my hiring example could generalize to cause areas where the output is primarily research and the costs are primarily income. E.g., everyone we’d identify to do more good than harm in AI safety research in expectation could already be funded (although maybe they could continue to use more compute cost-effectively?). The same could be true for grantmakers. Maybe we can just always hire more people who aren’t counterproductive in expectation, and the drop is just steep, and that’s fine since the stakes are astronomical.
You seem to be suggesting that Open Phil might be overfunding orgs so that their marginal dollars are not actually effective.
But Open Phil believes it can spend marginal dollars at ~7x GiveDirectly.
I think what’s happening is that Open Phil is taking up opportunities down to ~7x GiveDirectly, and so if small donors top up those orgs, those extra donations will be basically as effective as 7x GiveDirectly (in practice negligibly lower).
I agree with this for global health and poverty, but I expect the drop in cost-effectiveness to be much worse in the other big EA cause areas and especially in organizations where the vast majority of spending is on salaries.
There are no sharp cut offs—just gradually diminishing returns.
An org can pretty much always find a way to spend 1% more money and have a bit more impact. And even if an individual org appears to have a sharp cut off, we should really be thinking about the margin across the whole community, which will be smooth. Since the total donated per year is ~$400m, adding $1000 to that will be about equally as effective as the last $1000 donated.
You seem to be suggesting that Open Phil might be overfunding orgs so that their marginal dollars are not actually effective.
But Open Phil believes it can spend marginal dollars at ~7x GiveDirectly.
I think what’s happening is that Open Phil is taking up opportunities down to ~7x GiveDirectly, and so if small donors top up those orgs, those extra donations will be basically as effective as 7x GiveDirectly (in practice negligibly lower).
The marginal impact can be much smaller, but this depends on the particulars. I think hiring is the most important example, especially in cases where salaries make up almost all of the costs of the organization. Suppose a research organization hired everyone they thought was worth hiring at all (with their current management capacity as a barrier, or based on producing more than they cost managers, or based on whether they will set the org in a worse direction, etc.). Or, the difference between their last hire and their next hire could also be large. How would they spend an extra 1% similarly cost-effectively? I think you should expect a big drop in marginal cost-effectiveness here.
Maybe in many cases there are part-time workers you can get more hours from by paying them more.
I think my hiring example could generalize to cause areas where the output is primarily research and the costs are primarily income. E.g., everyone we’d identify to do more good than harm in AI safety research in expectation could already be funded (although maybe they could continue to use more compute cost-effectively?). The same could be true for grantmakers. Maybe we can just always hire more people who aren’t counterproductive in expectation, and the drop is just steep, and that’s fine since the stakes are astronomical.
I agree with this for global health and poverty, but I expect the drop in cost-effectiveness to be much worse in the other big EA cause areas and especially in organizations where the vast majority of spending is on salaries.