good points. This can also go the other way though—an org could leverage money from otherwise very ineffective orgs. Especially with policy changes, it can sometimes be the case that a good org comes up with a campaign that steers the entire advocacy ecosystem to a more effective path. A good example of this is campaigns for ordinary air pollution regulations on coal plants, which were started in the 1990s by the Clean Air Task Force among others and now have hundreds of millions in funding from Bloomberg. If these campaigns weren’t started, environmental NGOs in the US and Europe would plausibly be working on something much worse.
I don’t think the notion of ‘credit’ is a useful one. At FP, when we were looking at orgs working on policy change, we initially asked them how much credit they should take for a particular policy change. They ended up saying things like “40%”. I don’t really understand what this means. It turned out to be best to ask them when the campaign and policy change would have happened had they not acted (obviously a very difficult question). It’s best to couch things in terms of counterfactual impact throughout and not to convert into ‘credit’.
Similarly with voting, if an election is decided by one vote and there are one million voters for the winning party, I think it is inevitably misleading to ask how much of the credit each voter should get. One naturally answers that they get one millionth of the credit, but this is wrong as a proposition about their counterfactual impact, which is what we really care about.
Indeed, focusing on credit can lead you to attribute impact in cases of redundant causation when an org actually has zero counterfactual impact. Imagine 100 orgs are working for a big policy change, and only 50 of them were necessary to the outcome (though this could be any combination of them and they were all equally important). In this case, funding one of the orgs had zero counterfactual impact because the change would have happened without them. But on the ‘credit approach’, you’d end up attributing one hundredth of the impact to each of the orgs
I agree—I was talking a bit too loosely. When I said “assign credit of 30% of X” I meant “assign counterfactual impact of 30% of X”. My point was just that even if you do add up all the counterfactual impacts (ignoring that this is a conceptual mistake like you point out), they rarely sum to more than 100%, so it’s still not a big issue.
I’m not sure I follow the first paragraph about leveraging other groups.
You argued that counterfactual impact may be smaller than it appears. But it may also be larger than it first appears due to leveraging other orgs away from ineffective activities. e.g. an NGO successfully advocates for a policy change P1 - the benefits of P1 is their counterfactual impact. But as a result of the proven success of this type of project, 100 other NGOs start working on similar projects where before they worked on ineffective projects. This latter effect should also be counted as the first org’s counterfactual impact. This could be understood as leveraging additional money into an effective space.
I don’t agree. His logic entails that money/effort you leverage shouldn’t be counted as your own counterfactual impact. If FHI convinces e.g. the UK government that biorisk is worth spending money on, then on Joey’s approach, FHI would be wrong to count this additional money as it’s own impact.
good points. This can also go the other way though—an org could leverage money from otherwise very ineffective orgs. Especially with policy changes, it can sometimes be the case that a good org comes up with a campaign that steers the entire advocacy ecosystem to a more effective path. A good example of this is campaigns for ordinary air pollution regulations on coal plants, which were started in the 1990s by the Clean Air Task Force among others and now have hundreds of millions in funding from Bloomberg. If these campaigns weren’t started, environmental NGOs in the US and Europe would plausibly be working on something much worse.
I don’t think the notion of ‘credit’ is a useful one. At FP, when we were looking at orgs working on policy change, we initially asked them how much credit they should take for a particular policy change. They ended up saying things like “40%”. I don’t really understand what this means. It turned out to be best to ask them when the campaign and policy change would have happened had they not acted (obviously a very difficult question). It’s best to couch things in terms of counterfactual impact throughout and not to convert into ‘credit’.
Similarly with voting, if an election is decided by one vote and there are one million voters for the winning party, I think it is inevitably misleading to ask how much of the credit each voter should get. One naturally answers that they get one millionth of the credit, but this is wrong as a proposition about their counterfactual impact, which is what we really care about.
Indeed, focusing on credit can lead you to attribute impact in cases of redundant causation when an org actually has zero counterfactual impact. Imagine 100 orgs are working for a big policy change, and only 50 of them were necessary to the outcome (though this could be any combination of them and they were all equally important). In this case, funding one of the orgs had zero counterfactual impact because the change would have happened without them. But on the ‘credit approach’, you’d end up attributing one hundredth of the impact to each of the orgs
I agree—I was talking a bit too loosely. When I said “assign credit of 30% of X” I meant “assign counterfactual impact of 30% of X”. My point was just that even if you do add up all the counterfactual impacts (ignoring that this is a conceptual mistake like you point out), they rarely sum to more than 100%, so it’s still not a big issue.
I’m not sure I follow the first paragraph about leveraging other groups.
You argued that counterfactual impact may be smaller than it appears. But it may also be larger than it first appears due to leveraging other orgs away from ineffective activities. e.g. an NGO successfully advocates for a policy change P1 - the benefits of P1 is their counterfactual impact. But as a result of the proven success of this type of project, 100 other NGOs start working on similar projects where before they worked on ineffective projects. This latter effect should also be counted as the first org’s counterfactual impact. This could be understood as leveraging additional money into an effective space.
Makes sense. I don’t think Joey would object if orgs were counting this though.
I don’t agree. His logic entails that money/effort you leverage shouldn’t be counted as your own counterfactual impact. If FHI convinces e.g. the UK government that biorisk is worth spending money on, then on Joey’s approach, FHI would be wrong to count this additional money as it’s own impact.