Hey! Thanks for the comment! I really appreciate it. For some reason I’m only seeing it now and by chance. I don’t know if I didn’t get the notification or if I missed it.
Regarding the content of your comment: I agree with most of it. In fact 3.6 years is probably a big overestimation. However, I still think, in general, that bringing LEV forward could be a big contributor to the cost-effectiveness of aging research in general. In my newer post I lay your same arguments about improving technology that may subsume the effect of today’s research, making it less cost-effective. This factor also influences variable E in the TAME analysis, which I also probably vastly overestimated. 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.
Maybe I’m still less “pessimistic” than you in the sense that I think that an ice-breaking effect could enable more research on what are neglected facets of aging for which treatments could be devised much more quickly. 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.
Regarding the expected number of years added by metformin: I think “one year” is a very conservative number given the evidence I’ve presented, and you’ll often hear researchers estimating more.
Hey! Thanks for the comment! I really appreciate it. For some reason I’m only seeing it now and by chance. I don’t know if I didn’t get the notification or if I missed it.
I’m not sure if this is the post I was asking feedback for though. This analysis is from nine months ago, and my views on it changed. On Facebook I was probably referring to this other post I made recently: A general framework for evaluating aging research. Part 1: reasoning with Longevity Escape Velocity. [EDIT: I just saw you made a comment under that post too, so never mind].
Regarding the content of your comment: I agree with most of it. In fact 3.6 years is probably a big overestimation. However, I still think, in general, that bringing LEV forward could be a big contributor to the cost-effectiveness of aging research in general. In my newer post I lay your same arguments about improving technology that may subsume the effect of today’s research, making it less cost-effective. This factor also influences variable E in the TAME analysis, which I also probably vastly overestimated. 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.
Maybe I’m still less “pessimistic” than you in the sense that I think that an ice-breaking effect could enable more research on what are neglected facets of aging for which treatments could be devised much more quickly. 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.
Regarding the expected number of years added by metformin: I think “one year” is a very conservative number given the evidence I’ve presented, and you’ll often hear researchers estimating more.