Is it your impression that whenever you -or talented friends in this area- come up with a reasonably-implementable good idea, that after searching around, you tend to discover that someone else has already found it and tried it?
I think this is somewhat true, although I don’t think this (or the suggestions for bottlenecks in the paragraph below) quite hits the mark. The mix of considerations are something like these:
1) I generally think the existing community covers the area fairly competently (from an EA perspective). I think the main reason for this is because the ‘wish list’ of what you’d want to see for (say) a disease surveillance system from an EA perspective will have a lot of common elements with what those with more conventional priorities would want. Combined with the billions of dollars and lots of able professionals, even areas which are neglected in relative terms still tend to have well-explored margins.
1.1) So there are a fair few cases where I come across something in the literature that anticipates an idea I had, or of colleagues/collaborators reporting back, “It turns out people are already trying to do all the things I’d want them to do re. X”.
1.2) Naturally, given I’m working on this, I don’t think there’s no more good ideas to have. But it also means I foresee quite a lot of the value is rebalancing/pushing on the envelope of the existing portfolio rather than ‘EA biosecurity’ striking out on its own.
2) A lot turns on ‘reasonably-implementable’. There’s a generally treacherous terrain that usually lies between idea and implementation, and propelling the former to the latter through this generally needs a fair amount of capital (of various types). I think this is the typical story for why many fairly obvious improvements haven’t happened.
2.1) For policy contributions, perhaps the main challenge is buy-in. Usually one can’t ‘implement yourself’, and rely instead on influencing the relevant stakeholders (e.g. science, industry, government(s)) to have an impact. Bandwidth is generally limited in the best case, and typical cases tend to be fraught with well-worn conflicts arising from differing priorities etc. Hence the delicateness mentioned above.
2.2) For technical contributions, there are ‘up-front’ challenges common to doing any sort of bio-science research (e.g. wet-labs are very expensive). However, pushing one of these up the technology readiness levels to implementation also runs into similar policy challenges (as, again, you can seldom ‘implement yourself’).
3) This doesn’t mean there are no opportunities to contribute. Even if there’s a big bottleneck further down the policy funnel, new ideas upstream still have value (although knowing what the bottleneck looks like can help one target these to have easier passage—and not backfire), and in many cases there will be more incremental work which can lay the foundation for further development. There could be a synergistic relationship with folks who are more heavily enmeshed in the existing community can help translate initiatives/ideas from those less so.
Just wanted to say thanks to both Gregory and Spiracular for their detailed and thoughtful back and forth in this thread. As someone coming from a place somewhere in the middle but having spent less time thinking through these considerations, I found getting to hear your personal perspectives very helpful.
Thanks! For me, this does a bit to clear up why buy-in is perceived as such a key bottleneck.
(And secondarily, supporting the idea that other areas of fairly-high ROI are likely to be centered around facilitating collaboration and consolidation of resources among people with a lot of pre-existing experience/expertise/buy-in.)
Hello Spiracular,
I think this is somewhat true, although I don’t think this (or the suggestions for bottlenecks in the paragraph below) quite hits the mark. The mix of considerations are something like these:
1) I generally think the existing community covers the area fairly competently (from an EA perspective). I think the main reason for this is because the ‘wish list’ of what you’d want to see for (say) a disease surveillance system from an EA perspective will have a lot of common elements with what those with more conventional priorities would want. Combined with the billions of dollars and lots of able professionals, even areas which are neglected in relative terms still tend to have well-explored margins.
1.1) So there are a fair few cases where I come across something in the literature that anticipates an idea I had, or of colleagues/collaborators reporting back, “It turns out people are already trying to do all the things I’d want them to do re. X”.
1.2) Naturally, given I’m working on this, I don’t think there’s no more good ideas to have. But it also means I foresee quite a lot of the value is rebalancing/pushing on the envelope of the existing portfolio rather than ‘EA biosecurity’ striking out on its own.
2) A lot turns on ‘reasonably-implementable’. There’s a generally treacherous terrain that usually lies between idea and implementation, and propelling the former to the latter through this generally needs a fair amount of capital (of various types). I think this is the typical story for why many fairly obvious improvements haven’t happened.
2.1) For policy contributions, perhaps the main challenge is buy-in. Usually one can’t ‘implement yourself’, and rely instead on influencing the relevant stakeholders (e.g. science, industry, government(s)) to have an impact. Bandwidth is generally limited in the best case, and typical cases tend to be fraught with well-worn conflicts arising from differing priorities etc. Hence the delicateness mentioned above.
2.2) For technical contributions, there are ‘up-front’ challenges common to doing any sort of bio-science research (e.g. wet-labs are very expensive). However, pushing one of these up the technology readiness levels to implementation also runs into similar policy challenges (as, again, you can seldom ‘implement yourself’).
3) This doesn’t mean there are no opportunities to contribute. Even if there’s a big bottleneck further down the policy funnel, new ideas upstream still have value (although knowing what the bottleneck looks like can help one target these to have easier passage—and not backfire), and in many cases there will be more incremental work which can lay the foundation for further development. There could be a synergistic relationship with folks who are more heavily enmeshed in the existing community can help translate initiatives/ideas from those less so.
Just wanted to say thanks to both Gregory and Spiracular for their detailed and thoughtful back and forth in this thread. As someone coming from a place somewhere in the middle but having spent less time thinking through these considerations, I found getting to hear your personal perspectives very helpful.
Thanks! For me, this does a bit to clear up why buy-in is perceived as such a key bottleneck.
(And secondarily, supporting the idea that other areas of fairly-high ROI are likely to be centered around facilitating collaboration and consolidation of resources among people with a lot of pre-existing experience/expertise/buy-in.)