One issue I would add to your theoretical analysis: with assigning 1000+ QALYs to letting someone reach LEV is that people commonly don’t claim linear utility with lifespan, i.e. they would often prefer to live to 80 with certainty rather than die at 20 with 90% probability and live to 10,000 with 10% probability.
I agree it’s worth keeping the chance that people will be able to live much longer in the future in mind when assessing benefits to existing people (I would also add the possibility of drastic increases in quality of life through technology). I’d guess most of this comes from broader technological improvements (e.g. via AI) rather than reaching LEV through biomedical approaches), but not with extreme confidence.
However, I don’t think it has very radical implications for cause prioritization since, as you note, deaths for any reason (include malaria and global catastrophes) deny those people a chance at LEV. LEV-related issues are also mainly a concern for existing humans, so to the extent one gives a boost for enormous impacts on nonhuman animals and the existence of future generations, LEV speedup won’t reap much of those boosts.
Within the field of biomedical research, aging looks relatively promising, and I think on average the best-targeted biomedical research does well for current people compared to linear charity in support of deployment (e.g. gene drives vs bednets). But it’s not a slam dunk because the problems are so hard (including ones receiving massive investment). I don’t see it as strongly moving most people who prefer to support bednets over malaria gene drives, farmed animal welfare over gene drives, or GCR reduction over gene drives.
I just answered your other comment, but I saw this one only now. Apparently both notifications didn’t arrive. Thanks a lot for taking the time to read and answer both.
Some of my replies in the other comment apply here too. I’ll go in order.
Regarding your first paragraph: Yes, I’m preparing a post about potential age discounting that could be applied. I included it among the moral considerations that would correct impact. But you made a good point, and I may need to modify it in the light of it.
Regarding AI and other technology: For the very specific case of AI potentially automating R&D I think the timeline is longer than for LEV achieved through biomedical research (I’m taking the view that arises from the probability distribution given by AI researchers), but, as you said, it’s not the only technology that would make some of the efforts made now less useful.
Regarding your third paragraph: Yes, probably the only non-human animals benefitting from LEV would be pets, although I don’t know how many. I should try to do an estimate.
Regarding comparisons with other cause areas: I think there are some interventions in aging research that could reap massive benefits which are neglected and somewhat tractable. Copying from the other comment: The foundational research is not very neglected, while there are wide areas of translational research that could use much more funding and that are necessary to reach the final goal. From the lifespan.io’s Rejuvenation Roadmap you should get a preliminary idea.
Your example using the SENS approach is correct: areas like stem cell research and cancer research don’t seem to be underfunded. But they are only two pieces of the puzzle. Some others are being much more neglected. That’s why SENS itself gives higher priority to the most neglected areas, like mitochondrial dysfunction and crosslinks, which should be also more tractable (an interesting fact is that Aubrey de Grey often emphasises neglectedness, tractability and scope in his conferences, but I haven’t heard anyone within EA pointing this out). If stem cells research, cancer and other difficult and highly funded areas were all there is to aging research, it wouldn’t look like a very good candidate EA cause. In fact, not only de Grey but many researchers in the area are pursuing projects they believe are very much funding constrained (example: Steve Horvath).
About the comparison with x-risk reduction: Yes, I broadly agree that x-risk reduction looks overall more promising as a cause area. However I think that many x-risk focused interventions have a higher level of uncertainty. It also seems that within Effective Altruism little to no effort has been made to evaluate aging research, while, to me, it looks highly competitive with many of the other focuses of EAs (some specific interventions inside aging research should be very recognisably better). So it should be analysed further, especially because we may be missing out on especially important opportunities.
One issue I would add to your theoretical analysis: with assigning 1000+ QALYs to letting someone reach LEV is that people commonly don’t claim linear utility with lifespan, i.e. they would often prefer to live to 80 with certainty rather than die at 20 with 90% probability and live to 10,000 with 10% probability.
I agree it’s worth keeping the chance that people will be able to live much longer in the future in mind when assessing benefits to existing people (I would also add the possibility of drastic increases in quality of life through technology). I’d guess most of this comes from broader technological improvements (e.g. via AI) rather than reaching LEV through biomedical approaches), but not with extreme confidence.
However, I don’t think it has very radical implications for cause prioritization since, as you note, deaths for any reason (include malaria and global catastrophes) deny those people a chance at LEV. LEV-related issues are also mainly a concern for existing humans, so to the extent one gives a boost for enormous impacts on nonhuman animals and the existence of future generations, LEV speedup won’t reap much of those boosts.
Within the field of biomedical research, aging looks relatively promising, and I think on average the best-targeted biomedical research does well for current people compared to linear charity in support of deployment (e.g. gene drives vs bednets). But it’s not a slam dunk because the problems are so hard (including ones receiving massive investment). I don’t see it as strongly moving most people who prefer to support bednets over malaria gene drives, farmed animal welfare over gene drives, or GCR reduction over gene drives.
I just answered your other comment, but I saw this one only now. Apparently both notifications didn’t arrive. Thanks a lot for taking the time to read and answer both.
Some of my replies in the other comment apply here too. I’ll go in order.
Regarding your first paragraph: Yes, I’m preparing a post about potential age discounting that could be applied. I included it among the moral considerations that would correct impact. But you made a good point, and I may need to modify it in the light of it.
Regarding AI and other technology: For the very specific case of AI potentially automating R&D I think the timeline is longer than for LEV achieved through biomedical research (I’m taking the view that arises from the probability distribution given by AI researchers), but, as you said, it’s not the only technology that would make some of the efforts made now less useful.
Regarding your third paragraph: Yes, probably the only non-human animals benefitting from LEV would be pets, although I don’t know how many. I should try to do an estimate.
Regarding comparisons with other cause areas: I think there are some interventions in aging research that could reap massive benefits which are neglected and somewhat tractable. Copying from the other comment: The foundational research is not very neglected, while there are wide areas of translational research that could use much more funding and that are necessary to reach the final goal. From the lifespan.io’s Rejuvenation Roadmap you should get a preliminary idea.
Your example using the SENS approach is correct: areas like stem cell research and cancer research don’t seem to be underfunded. But they are only two pieces of the puzzle. Some others are being much more neglected. That’s why SENS itself gives higher priority to the most neglected areas, like mitochondrial dysfunction and crosslinks, which should be also more tractable (an interesting fact is that Aubrey de Grey often emphasises neglectedness, tractability and scope in his conferences, but I haven’t heard anyone within EA pointing this out). If stem cells research, cancer and other difficult and highly funded areas were all there is to aging research, it wouldn’t look like a very good candidate EA cause. In fact, not only de Grey but many researchers in the area are pursuing projects they believe are very much funding constrained (example: Steve Horvath).
About the comparison with x-risk reduction: Yes, I broadly agree that x-risk reduction looks overall more promising as a cause area. However I think that many x-risk focused interventions have a higher level of uncertainty. It also seems that within Effective Altruism little to no effort has been made to evaluate aging research, while, to me, it looks highly competitive with many of the other focuses of EAs (some specific interventions inside aging research should be very recognisably better). So it should be analysed further, especially because we may be missing out on especially important opportunities.