Thank you for the post – very interesting and thought provoking ideas. I have a couple of points to explore further that I’ll break into different replies.
I’d be curious for more thoughts on how common these situations are.
In the climate change, AI safety, conservation example, it occurred to me that if each individual thinks that their top option is 10 times more effective than the second option, it becomes clearly better again (from their pov) to support their top option. The numbers seem to only work because AI safety is marginally better than climate change.
You point out that the problem becomes more severe as the number of funders increases. It seems like there are roughly 4 ‘schools’ of EA donors, so if we consider a coordination problem between these four schools, it’ll roughly make the issue 2x bigger, but it seems like that still wouldn’t outweigh 10x differences in effectiveness.
I’d be interested in more thoughts on how commonly we’re in the prisoner’s dilemma situation you note, and what the key variables are (e.g. differences in cause effectiveness, number of funders etc.).
Thanks a lot for the comment. Here are a few points:
1. You’re right that the simple climate change example it won’t always be a prisoner’s dilemma. However, I think that’s more due to the fact that I assumed constant returns to scale for all three causes. At the bottom of this write-up I have an example with three causes that all have log returns. As long as both funders value the causes positively and don’t have identical valuations, a pareto improvement is possible through cooperation (unless I’m making a mistake in the proof, which is possible). So I think the existence of collective action problems is more general than the climate change example would make it seem.
2. It’s a very nice point that the gains from cooperation may be small in magnitude, even if they’re positive. That is definitely possible. But I’m a little skeptical that large valuation differences between the 4 ‘schools’ of EA donors means that the gains to cooperation are likely to be small. I think even within those schools there are significant disagreements among causes. For example, within the long-termist school, disagreements on whether we’re living in an extremely influential time or on how to value population increases can lead to very large disagreements in valuation of causes. Also, when people have very large differences in valuations of direct causes, the opportunity for conflict on the advocacy front seems to increase (See Phil Trammell’s post here).
I agree that it would be useful to get more of an idea of when the prisoner’s dilemma is likely to be severe. Right now I don’t think I have much more to add on that.
At the bottom of this write-up I have an example with three causes that all have log returns. As long as both funders value the causes positively and don’t have identical valuations, a pareto improvement is possible through cooperation.
Thank you for the post – very interesting and thought provoking ideas. I have a couple of points to explore further that I’ll break into different replies.
I’d be curious for more thoughts on how common these situations are.
In the climate change, AI safety, conservation example, it occurred to me that if each individual thinks that their top option is 10 times more effective than the second option, it becomes clearly better again (from their pov) to support their top option. The numbers seem to only work because AI safety is marginally better than climate change.
You point out that the problem becomes more severe as the number of funders increases. It seems like there are roughly 4 ‘schools’ of EA donors, so if we consider a coordination problem between these four schools, it’ll roughly make the issue 2x bigger, but it seems like that still wouldn’t outweigh 10x differences in effectiveness.
The point about advocacy making it worse seems good, and a point against advocacy efforts in general. Paul Christiano also made a similar point here: https://rationalaltruist.com/2013/06/13/against-moral-advocacy/
I’d be interested in more thoughts on how commonly we’re in the prisoner’s dilemma situation you note, and what the key variables are (e.g. differences in cause effectiveness, number of funders etc.).
Thanks a lot for the comment. Here are a few points:
1. You’re right that the simple climate change example it won’t always be a prisoner’s dilemma. However, I think that’s more due to the fact that I assumed constant returns to scale for all three causes. At the bottom of this write-up I have an example with three causes that all have log returns. As long as both funders value the causes positively and don’t have identical valuations, a pareto improvement is possible through cooperation (unless I’m making a mistake in the proof, which is possible). So I think the existence of collective action problems is more general than the climate change example would make it seem.
2. It’s a very nice point that the gains from cooperation may be small in magnitude, even if they’re positive. That is definitely possible. But I’m a little skeptical that large valuation differences between the 4 ‘schools’ of EA donors means that the gains to cooperation are likely to be small. I think even within those schools there are significant disagreements among causes. For example, within the long-termist school, disagreements on whether we’re living in an extremely influential time or on how to value population increases can lead to very large disagreements in valuation of causes. Also, when people have very large differences in valuations of direct causes, the opportunity for conflict on the advocacy front seems to increase (See Phil Trammell’s post here).
I agree that it would be useful to get more of an idea of when the prisoner’s dilemma is likely to be severe. Right now I don’t think I have much more to add on that.
Very interesting, thank you.