There needs to be more willingness by grantwriters and other funders to bear search-costs for new ideas. It seems like there is a strong emphasis on skepticism within EA, which is great, but it usually translates to, we should not fund this because of perceived issues X, Y, and Z or uncertainty regarding the benefits of A, B, and C, when these issues and benefits are better addressed through empirical testing than a skepticâs intuitions. We need a community that will bear the discovery costs of promising interventions, but this seldom happens unless the proponent of the idea already has clout and/âor connections within EA.
If we donât have the information to evaluate the effectiveness of a possible solution, the answer is not to discard a potential solution, but rather evaluate the information costs, and the potential value associated with the array of reasonably possible outcomes.
What would be helpful, if this doesnât exist, would be aggregating sets of potential solutions, listing the resources currently directed toward evaluating their EV, determining bottlenecks (often money) in assessing EV, and making reasonable estimates of potential exploitation values given various hypothesize EV. Then those with resources in EA could ensure that promising paths have the resources to be explored, and we can exploit the best solutions fully.
I am rather pessimistic about EAâs prospects for this.
Why are you pessimistic? I assume it has something to do with perceived power dynamics or incentive misalignment?
It seems like a crowd sourcing mechanism for potential solutions, plus a small team to manage the data and make estimates on expected info cost, actual cost, and impact, would be fairly simple to implement.
Maybe one could even lean harder into crowdsourcing the info/âactual costs and impact by operating a sort of prediction market on it, so if a solution is indeed researched at some point and your prediction of the info and actual estimated costs was correct/âclose, you get points and higher weighting in future crowdsourced estimates?
Although I donât necessarily endorse it, the argument against investing in new cause areas that arenât a significant existential risk within a few decades is straightforward. Therefore, any cause prioritization project should address this objection with a counter-rebuttal, or else pessimism is warranted.
Good point. Iâd imagine that this objection stems from the perspective âbasically all the highest utility/âdollar interventions are in x-risk, but continuing global health interventions costs us little because we already have those systems in place, so itâs not worth abandoning them.â
From this perspective, one might think that even maintaining existing global health interventions is a bad util/âdollar proposition in a vacuum (as those resources would be better spent on x-risk), but for external reasons, splintering EA is not worth pressuring people to abandon global health.
Letâs imagine splintering EA to mean nearly only x-riskers being left in EA, and maybe a group of dissidents creating a competing movement.
These are the pros for x-riskers post-split:
Remaining EAs are laser-focused on x-risk, and perhaps more people have shifted their focus from partly global health and partly x-risk to fully x-risk than vice versa. (More x-risk EAs and x-risk EAs are more effective).
These are the cons for x-riskers post-split:
Remaining EAs have less broad public support and less money going into âgeneral EA stuffâ like community building and conferences, because some of the general EA money and influence was coming from people who mostly cared about global health. As a related consequence, it becomes harder to attract people initially interested in global health and convert them into x-riskers. (Less x-risk EAs and x-risk EAs are less effective).
It seems that most x-riskers think the cons outweigh the pros, or a split would have occurredâat least there would be more talk of one.
The thing is, refraining from adding climate change as an EA focus would likely have a similar pro/âcon breakdown to removing global health as an EA focus:
Pros: No EAs are persuaded to put money/âeffort that might have gone to x-risk into climate change.
Cons:
Loss of utils due to potentially EA-compatible people who expend time or money on climate change prevention/âmitigation not joining the movement and adopting EA methods.
Loss of potential general funding and support for EA from people who think that the top climate change interventions can compete with the util/âdollar rates of top global health and x-risk interventions, plus the hordes of people who arenât necessarily thinking in terms of utils/âdollar yet and just instinctively feel climate change is so important that a movement ignoring it canât possibly know what theyâre doing. Even if someone acting on instinct rather than utils/âdollar wonât necessarily improve the intellectual richness of EA, their money and support would be pretty unequivocally helpful.
These are basically the same pros and cons to kicking out global health people, plus an extra cost to not infiltrating another cause area with EA methods.
Therefore, I would argue that any x-risker that does not want to splinter EA should also support EA branching out into new areas.
I think this is a totally reasonable argument, and you can add a piece thatâs about personal fit. Like 80,000 hours has pretty arbitrarily guesstimated how heavily one ought to weigh personal fit in career choice, slapped some numbers on it and published it in a prioritization scale that people take too seriously sometimes and doesnât actually make sense if you actually look at what some of the numbers imply (ie everybody should work on AI safety even if an actively bad fit).
But if you start by weighing personal fit more highly, there becomes a case for saying âok, I happen to care a lot about climate change, so even if itâs not the highest priority cause, itâs still what I personally ought to work on. And I need guidance about how to move the needle on climate change.â And if you start from there you can still do a whole EA solutions prioritization analysis just taking for granted that it will be 100% climate change focused.
Personally I suspect thatâs a good solutionâwe have great ideas about how to prioritize stuff but Iâm not very optimistic about our ability to fundamentally change what causes people work on. Like maybe people should work on AI x risk even if theyâre an actively bad fit, but they wonât, and we shouldnât waste time trying to convince them to. Instead we should just create a great on-ramp for people who are interested in AI safety and a second great on-ramp for people who are interested in climate change. Figure out where people are and are not flexible in what they work on and target that.
There needs to be more willingness by grantwriters and other funders to bear search-costs for new ideas. It seems like there is a strong emphasis on skepticism within EA, which is great, but it usually translates to, we should not fund this because of perceived issues X, Y, and Z or uncertainty regarding the benefits of A, B, and C, when these issues and benefits are better addressed through empirical testing than a skepticâs intuitions. We need a community that will bear the discovery costs of promising interventions, but this seldom happens unless the proponent of the idea already has clout and/âor connections within EA.
If we donât have the information to evaluate the effectiveness of a possible solution, the answer is not to discard a potential solution, but rather evaluate the information costs, and the potential value associated with the array of reasonably possible outcomes.
What would be helpful, if this doesnât exist, would be aggregating sets of potential solutions, listing the resources currently directed toward evaluating their EV, determining bottlenecks (often money) in assessing EV, and making reasonable estimates of potential exploitation values given various hypothesize EV. Then those with resources in EA could ensure that promising paths have the resources to be explored, and we can exploit the best solutions fully.
I am rather pessimistic about EAâs prospects for this.
Why are you pessimistic? I assume it has something to do with perceived power dynamics or incentive misalignment?
It seems like a crowd sourcing mechanism for potential solutions, plus a small team to manage the data and make estimates on expected info cost, actual cost, and impact, would be fairly simple to implement.
Maybe one could even lean harder into crowdsourcing the info/âactual costs and impact by operating a sort of prediction market on it, so if a solution is indeed researched at some point and your prediction of the info and actual estimated costs was correct/âclose, you get points and higher weighting in future crowdsourced estimates?
Although I donât necessarily endorse it, the argument against investing in new cause areas that arenât a significant existential risk within a few decades is straightforward. Therefore, any cause prioritization project should address this objection with a counter-rebuttal, or else pessimism is warranted.
Good point. Iâd imagine that this objection stems from the perspective âbasically all the highest utility/âdollar interventions are in x-risk, but continuing global health interventions costs us little because we already have those systems in place, so itâs not worth abandoning them.â
From this perspective, one might think that even maintaining existing global health interventions is a bad util/âdollar proposition in a vacuum (as those resources would be better spent on x-risk), but for external reasons, splintering EA is not worth pressuring people to abandon global health.
Letâs imagine splintering EA to mean nearly only x-riskers being left in EA, and maybe a group of dissidents creating a competing movement.
These are the pros for x-riskers post-split:
Remaining EAs are laser-focused on x-risk, and perhaps more people have shifted their focus from partly global health and partly x-risk to fully x-risk than vice versa. (More x-risk EAs and x-risk EAs are more effective).
These are the cons for x-riskers post-split:
Remaining EAs have less broad public support and less money going into âgeneral EA stuffâ like community building and conferences, because some of the general EA money and influence was coming from people who mostly cared about global health. As a related consequence, it becomes harder to attract people initially interested in global health and convert them into x-riskers. (Less x-risk EAs and x-risk EAs are less effective).
It seems that most x-riskers think the cons outweigh the pros, or a split would have occurredâat least there would be more talk of one.
The thing is, refraining from adding climate change as an EA focus would likely have a similar pro/âcon breakdown to removing global health as an EA focus:
Pros: No EAs are persuaded to put money/âeffort that might have gone to x-risk into climate change.
Cons:
Loss of utils due to potentially EA-compatible people who expend time or money on climate change prevention/âmitigation not joining the movement and adopting EA methods.
Loss of potential general funding and support for EA from people who think that the top climate change interventions can compete with the util/âdollar rates of top global health and x-risk interventions, plus the hordes of people who arenât necessarily thinking in terms of utils/âdollar yet and just instinctively feel climate change is so important that a movement ignoring it canât possibly know what theyâre doing. Even if someone acting on instinct rather than utils/âdollar wonât necessarily improve the intellectual richness of EA, their money and support would be pretty unequivocally helpful.
These are basically the same pros and cons to kicking out global health people, plus an extra cost to not infiltrating another cause area with EA methods.
Therefore, I would argue that any x-risker that does not want to splinter EA should also support EA branching out into new areas.
I think this is a totally reasonable argument, and you can add a piece thatâs about personal fit. Like 80,000 hours has pretty arbitrarily guesstimated how heavily one ought to weigh personal fit in career choice, slapped some numbers on it and published it in a prioritization scale that people take too seriously sometimes and doesnât actually make sense if you actually look at what some of the numbers imply (ie everybody should work on AI safety even if an actively bad fit).
But if you start by weighing personal fit more highly, there becomes a case for saying âok, I happen to care a lot about climate change, so even if itâs not the highest priority cause, itâs still what I personally ought to work on. And I need guidance about how to move the needle on climate change.â And if you start from there you can still do a whole EA solutions prioritization analysis just taking for granted that it will be 100% climate change focused.
Personally I suspect thatâs a good solutionâwe have great ideas about how to prioritize stuff but Iâm not very optimistic about our ability to fundamentally change what causes people work on. Like maybe people should work on AI x risk even if theyâre an actively bad fit, but they wonât, and we shouldnât waste time trying to convince them to. Instead we should just create a great on-ramp for people who are interested in AI safety and a second great on-ramp for people who are interested in climate change. Figure out where people are and are not flexible in what they work on and target that.