First—thank you for this. I currently research some aspects of resilience & adaptation and am asking myself some critical questions in this area. It also gave me something to build on and respond to, as a nudge to participate for the first time in the Forum, even if my thinking on this is underdeveloped!
On the post itself—I think the biggest contribution here is zooming out in the ending notes, to potential areas for EAs in a climate/longtermism space. What I took away was:
indirect x-risk from climate change is potentially important and neglected
as a group, some EAs interested in climate x longtermism should “pursue research ranking various climate interventions from a climate x-risk perspective”—I may have broadened this out to something like “more holistically assess how climate mitigation and adaptation solutions could indirectly impact total x-risk”
I have a lot of scattered further thoughts on this, but they’re underdeveloped, I’m very uncertain about them, and it’s likely I am missing some key EA literature/thinking already done on this. The central themes are that:
ranking climate problems/interventions for their indirect impacts on total x-risk is less tractable than addressing “direct” x-risk because it would require dealing with complexity i.e. a lot of feedback loops over time (and potentially space)
to my knowledge we (EA, but also humanity) don’t have many formal tools to deal with complexity/feedback loops/emergence, especially not at a global scale with so many different types of flows
there seem to be a lot of skills/attitudes/expertise in the EA community that would make us (as a group) particularly good at developing methodologies to deal with ambiguity/complex problems;
some time could be spent to scope what we can reasonably incorporate into a methodology that could deal with that complexity. The result might be that we decide any methodology aimed at this would require too much effort to do in practice, for the added information it gains (if it gains any), and so we decide dealing with “direct” x-risk only is still the best strategy with updated confidence. The result might also be that we come up with an extra verification that we aren’t missing something substantial when considering only direct risks—this could be as resource-intensive as detailed multi-modelling, or something ‘simpler’ like taking the GCR classification in Table 1 here and describing a set of timelines that test what happens when they interact with each other at a high level
In short I really appreciated the direction of your post! However I was less confident in how you got to those specific scenarios. I think progress in this area could include some standardised approach to generating them, and I think this might be important to establish before we’re able to confidently rank problems/solutions for indirect x-risk.
Again, it’s likely I’m missing key EA thinking/literature on this and I would love for anyone to make recommendations/corrections.
Terribly sorry for the late reply! I didn’t realize I missed replying to this comment.
I appreciate your kind words, and I think your thoughts are very eloquent and ultimately tackle a core epistemic challenge:
to my knowledge we (EA, but also humanity) don’t have many formal tools to deal with complexity/feedback loops/emergence, especially not at a global scale with so many different types of flows … some time could be spent to scope what we can reasonably incorporate into a methodology that could deal with that complexity.
First—thank you for this. I currently research some aspects of resilience & adaptation and am asking myself some critical questions in this area. It also gave me something to build on and respond to, as a nudge to participate for the first time in the Forum, even if my thinking on this is underdeveloped!
On the post itself—I think the biggest contribution here is zooming out in the ending notes, to potential areas for EAs in a climate/longtermism space. What I took away was:
indirect x-risk from climate change is potentially important and neglected
as a group, some EAs interested in climate x longtermism should “pursue research ranking various climate interventions from a climate x-risk perspective”—I may have broadened this out to something like “more holistically assess how climate mitigation and adaptation solutions could indirectly impact total x-risk”
I have a lot of scattered further thoughts on this, but they’re underdeveloped, I’m very uncertain about them, and it’s likely I am missing some key EA literature/thinking already done on this. The central themes are that:
ranking climate problems/interventions for their indirect impacts on total x-risk is less tractable than addressing “direct” x-risk because it would require dealing with complexity i.e. a lot of feedback loops over time (and potentially space)
to my knowledge we (EA, but also humanity) don’t have many formal tools to deal with complexity/feedback loops/emergence, especially not at a global scale with so many different types of flows
there seem to be a lot of skills/attitudes/expertise in the EA community that would make us (as a group) particularly good at developing methodologies to deal with ambiguity/complex problems;
some time could be spent to scope what we can reasonably incorporate into a methodology that could deal with that complexity. The result might be that we decide any methodology aimed at this would require too much effort to do in practice, for the added information it gains (if it gains any), and so we decide dealing with “direct” x-risk only is still the best strategy with updated confidence. The result might also be that we come up with an extra verification that we aren’t missing something substantial when considering only direct risks—this could be as resource-intensive as detailed multi-modelling, or something ‘simpler’ like taking the GCR classification in Table 1 here and describing a set of timelines that test what happens when they interact with each other at a high level
In short I really appreciated the direction of your post! However I was less confident in how you got to those specific scenarios. I think progress in this area could include some standardised approach to generating them, and I think this might be important to establish before we’re able to confidently rank problems/solutions for indirect x-risk. Again, it’s likely I’m missing key EA thinking/literature on this and I would love for anyone to make recommendations/corrections.
Terribly sorry for the late reply! I didn’t realize I missed replying to this comment.
I appreciate your kind words, and I think your thoughts are very eloquent and ultimately tackle a core epistemic challenge:
I recently wrote a new forum post on a framework/phrase I used tying together concepts from complexity science & EA, arguing that it can be used to provide tractable resilience-based solutions to complexity problems.