When I came to know the Effective Altruism movement in 2016 I was immediately captured. I currently have a CS degree and an interest in longevity, among many other things. I would like to make a positive impact.
Emanuele_Ascani
This is one of the best posts I’ve read here, wow.
One of the main things that concern me is that malevolent people could appropriate the concept of malevolence itself and start a witch hunt for people who have nothing to do with malevolence. This was passingly mentioned when acknowledging that political leaders could brand their opponents as malevolent. Overall I think this post makes a good job of outlining the pros and cons, but I just wanted to write this consideration in a comment because it has been somewhat prominent in my mind.
From hearing de Grey speak, you might get the impression that the scientific community has deftly avoided studying ageing. This is not the case; it has been studied for some time.
It’s weird that you got this impression, because in many TED Talks de Grey explicitly mentions that biogerontology has more than a century of history. It’s his approach to be new, together with the attitude of aging research as translational research instead of just basic non-translational biology research. When, for example, The Buck Institute was founded 20 years ago, it was frowned upon to think about aging research as a translational field, and the whole discipline was much smaller.
Regarding antagonistic pleiotropy: be careful not to mix theories explaining different causal levels of aging. Antagonistic pleiotropy explains some of the processes that lead to damage, but doesn’t say anything about damage itself. Aubrey de Grey’s categorization of damage is actually more accepted than ever. The scientific consensus is settled on something very close to it, described in the landmark paper “The Hallmarks of Aging”, from 2013.
I don’t know who you heard criticizing de Grey so harshly, but that’s very uncommon now. It happened in the early 2000s but not now. SENS Research Foundation, in fact, works with many universities and established institutions.
I highly suggest to read my new post about SENS Research Foundation that I just published here. I delve deep in these topics and more. I also plan to interview Dr. de Grey, and you will find some potential interview questions.
For me there is a strong “what the world could be if I did this, so it would be a huge waste if I didn’t do this” sense that motivates me, although in the past I used to overestimate the potential good effects of my actions. I think it is probably similar to the need for efficiency you mention, but it also generates an unpleasant but correct sense of urgency, because usually if I don’t do things fast, the effect could not be the same. There’s also wanting to have a good impact in the world, which is more core and generates meaning.
I’m surprised that “cost-effectiveness evaluation” doesn’t exist yet.
Some others that it’s weird enough that they don’t exist yet: “meta-charities”, “advocacy”, “pandemic preparedness”.
A couple of tags that would apply to all of my posts: “aging research”, “scientific research”.
Thanks for this post, strongly upvoted. The amount of attention (and funding) aging research gets within EA is unbelievably low. That’s why I wrote an entire series of posts on this cause-area. A couple of comments:
1) Remember: if a charity finances aging research, it has the effect of hastening it, not enabling it. Aging will be brought under medical control at some point, we are only able to influence when. This translates into the main impact factor of hastening the arrival of Longevity Escape Velocity.
2) Now look again at your bulleted list of “big” indirect effects, and remember that you can only hasten them, not enable them. To me, this consideration make the impact we can have on them seem no more than a rounding error if compared to the impact we can have due to LEV (each year you bring LEV closer by saves 36,500,000 lives of 1000QALYS. This is a conservative estimate I made here.)
Small correction: Aubrey de Grey only estimates a 50⁄50 chance of LEV within 17 years. This is also conditional on funding, because before the private money started to pour in five years ago, his estimate had been stuck for many years at 50⁄50 chance of LEV within 20-22 years.
Hey, this is a great post! I’m really happy to see it, and it was a really nice and unexpected surprise.
I don’t know if you have seen it, but I recently published the first post of a (will be) series in which I’m trying to build a framework for evaluating the cost-effectiveness of any given aging research/project: this one.
In your model you only account for DALYs prevented for measuring impact, while I would like to account for many more things: all the considerations arising from the concept of Longevity Escape Velocity (e.g. bringing its date closer by one year could save roughly 36,500,000 lives of 1000QALYs each, using a conservative estimate), DALYs prevented, the economic and societal benefits of increased healthspan (the longevity dividend), the value of information.
I would also like to explore moral considerations that could potentially influence impact, such as if age discounting has to be applied and how population ethics influence the estimates, since at a first glance an impersonal view seems to imply that a sharp downward correction is necessary (although upon further analysis it turns out that this is not the case).
Another difference is that I’m trying to build the tools for evaluating specific interventions inside this cause area, and not strictly the cause area as a whole. I’m taking this approach since I believe there are some interventions that would be very ineffective to fund and others that would be extraordinarily cost-effective.
One implication of this is how I will measure tractability and neglectedness: to estimate neglectedness I will probably use the arguments OpenPhilanthropy’s made on the topic but with an important addition: it would be informational to list the organisations working on facets of aging that are the least further along in the pipeline that goes from in vitro research to clinical application. We can probably start from the lifespan.io’s Rejuvenation Roadmap to build a list of this kind. For evaluating tractability there will be probably some scientific arguments to make.
At the end I will also analyse specific non-profits and interview some people.
In case you want to take a glance on what I’m currently writing, I gave you access to my current drafts (which are not polished at all, but may give you an idea of how I’m proceeding): this, this and this.
P.s: Nine months ago I also made this estimate of the expected cost per life saved of the TAME trial. It’s not great, but it may be of interest. It was made before I begun thinking about the framework.
Edit: Are you planning on doing other cost-effectiveness estimates on this topic? Should we unite forces?
- 28 Apr 2019 10:39 UTC; 1 point) 's comment on Aging research and population ethics by (
Could be, or could be the usual causation=/=correlation problem, or the usual study that doesn’t replicate. What study are you referring to?
It seems to me that the EV of financing cellular reprogramming research and aging clocks dropped significantly. There are many other very neglected and promising areas.
That said, the case that “billionaires are going to finance all this anyway” did seem to get stronger regardless, because now there’s a higher chance that other neglected areas will be included in such funding.How much higher though? This is not the first billionaire-led longevity initiative. What makes me more hopeful compared to other past initiatives is that this new company might be more focused on getting translational research done given the choice of topics and people involved. And also I wonder if the time is riper than in 2013 for other billionaires to start imitating these efforts, although it seems to be more of a PR risk for billionaires to take than in the past.
PR risk is just perceived though, I wonder how real of a problem it is for billionaires in this case. It seems to me that billionaires are hated regardless, and longevity research is an excuse to be more vocal about it. I wonder if they are realizing this. The PR damage might be to research rather than to billionaires. See AppliedDivinityStudies’ comment.
I will only write a comment and not an answer because I think other people will probably give better answers. The thinking probably includes that 1) the world was unprepared, therefore even if there is a massive effort going on, cheap opportunities to do good might arise. 2) This situation might somewhat change the equilibriums between cause-areas and within EA, also changing how the world responds to risk, which may influence what is neglected and what is not, for example. Here a good post by Peter Hurford.
About the lockdown: I find it difficult to evaluate the short term effects, but thinking about the very long term effects is also probably interesting. On the one hand, under the longtermist view, slowing down technological progress has enormous negative consequences for the far future if the slope of progress continues to be positive. On the other, a lockdown means that the world will take pandemic preparedness more seriously, which in turn diminishes the probability of existential risk, which should lead to a greater positive impact… so, maybe the answer should be “enough lockdown for this situation to improve our chances to face greater threats”? I recognize this is not exactly what you asked though.
Interesting overall, but I’ll never be tired of repeating that the majority of impact of aging research comes from making Longevity Escape Velocity come faster. This puts aging research in a much better position as a cause area than short or medium term causes. Not sure why literally everyone in the EA movement continues to ignore this metric completely. It just doesn’t make sense.
It’s not a matter of fairness. It’s a matter of reducing the probability of not hearing good ideas because of stupid reasons.
I agree.
I used “Counterintuitive”, because people tend to think the person-affecting view generates more cost-effectiveness than the impersonal view (see comments under my first post), regardless of how the views affect the comparison with other causes. But yes, adopting the person-affective view seems to make aging research look better in comparison to the other causes you mention, since it negates a lot of their impact. Instead, adopting the impersonal view makes the comparison favour prevention of x-risks that could wipe out literally all of humanity (otherwise aging research looks far better), and probably some interventions regarding non-human animals, also depending on how much you value animals.
Note that this doesn’t make aging research worthless to evaluate from an EA perspective. Many people and orgs (eg. Open Philanthropy) donate to more than just two top causes… and aging research seems to be second or third place, probably depending on how much you value non-human animals. Mathematically, it makes sense to differentiate between various top causes in order to reduce risk. Differentiating also makes sense when there are single specific interventions, in a seemingly worse causa area, that may nonetheless be more cost-effective than available interventions in a cause-area that overall looks better, which includes cases in which the more cost-effective interventions in the top cause-areas are funded, or if there are particularly cost-effective interventions in the seemingly worse cause-area.
It seems that now it is possible to upvote my own posts anonymously. The eternal question naturally rises: should I? In theory I think my post is useful, otherwise I wouldn’t have posted it, but at the same time if I upvote it, it feels like giving a high-five to myself. On a more serious note: is this a bug or a feature?
Relatedly, here’s another example of the kind of headlines you mention: https://futurism.com/neoscope/aging-unstoppable-youth
The fact that it’s on an online newspaper called “Futurism” is even more eye-popping.
One positive thing this might lead to is if people on the fence start to be actually more positive about weird future-related stuff given the hysteria of such headlines. But I have no idea. Might be wishful thinking.
How much time do you spend on forecasting, including researching the topics?
The fact that no new hallmark has been discovered in decades is probably telling. But I think it is reasonable to believe that there are different hallmarks that will be visible in longer-than-human lifespans.
Thanks for this post! I didn’t realise a description could be important. I added one :)
Thanks Mati_Roy and aarongertler for the suggestion of adding a summary. Now there is one!
Maty_Roy, thank you for the points made! I would like to correct what I think are a couple of misunderstandings and I would like to elaborate on your idea about using Death Escape Velocity, instead of Longevity Escape Velocity:
Misunderstandings:
1) 36,500,000 are the people dying of aging in a year, so bringing LEV closer by one year (and not by one day) would save this number of lives.
2) If Longevity Escape Velocity doesn’t happen, bringing the date in which aging is cured completely closer could simply do nothing. This because people living at that time could have already a really low risk of death, that can’t go much further down with an additional improvement on treatments for aging. This because if Longevity Escape Velocity doesn’t happen, then I would expect the “very slow scenario” or the “dire roadblocks” scenario to be true, and aging would be eradicated really slowly, possibly in centuries.
The points about why my estimate is conservative are summarised well, thanks for doing that :)
Regarding the idea of using “death escape velocity”: I didn’t use it because technologies that would decrease the risk of death by other causes other than aging are substantially different from the ones brought about by aging research. So it would be another cause area completely! I also would expect them to become more relevant in the future. I think there is not much use of thinking about them now and they wouldn’t make potential EA interventions to fund, since our ideas will be probably be made useless by potentially much better technology existing after aging gets eradicated (that is the first step). “Death escape velocity”could be brought about, for example, by friendly AGI, if that ever comes about. I think this input is valuable though, since it’s an existing related concept that is not talked about much.
Here how I would reason about moral weights in this case:
In this case the definition of a “life saved” is pretty different than what normally means. Normally a life saved means 30 to 80 DALYs averted, depending if the intervention is on adults or children. In this case we are talking about potentially thousands of DALYs averted, so a life saved should count more. On the other hand there’s also to take into consideration that when saving, for example, children who would have died of malaria, you are also giving them a chance of reaching LEV. It’s not a full chance as in the present evaluation, but something probably ranging from 30% to 70%.
Additional consideration: some people may want to consider children more important to save than adults. Introducing age weighting and time discounting could seem reasonable in this case, since even if you save 5000 DALYs you are only saving one person, so you might want to discount DALYs saved later in life. On the other hand there are reasons to disagree with this approach: Saving an old person and guaranteeing him/her to reach LEV means also “saving a library”. A vast amount of knowledge and experience, especially future experience would have been otherwise completely destroyed. In fact I am not so sure I would apply time discounting myself for this reason.
Regarding bayesian discounting:
I just read how GiveWell would go about this (https://blog.givewell.org/2011/08/18/why-we-cant-take-expected-value-estimates-literally-even-when-theyre-unbiased/). To account for it I would need a prior distribution (or more than one?). I also have difficulty making the calculation, since Guesstimate doesn’t let me calculate the variance of the random variables. I will try with other means… maybe with smaller data sets and proceeding by hand or using online calculators.
I would also like to introduce probability distributions in the whole analysis and turn some arguments made in the explanations of some variables in variables in their own right, and I would like to add some more informations (for example the safety profile and history of metformin and the value of information of the trial) based on feedback I’m receiving. This would mean rewriting many sections though, and this will require time.
For now I put an “Edit” at the beginning in order to warn readers not to take the numbers reached too seriously, but I invited them to delve in some more broadly applicable ideas I presented in the analysis that could be useful for evaluating many interventions in the cause area of aging.
Yeah, seriously, William MacAskill just change your surname already. It’s basic SEO for Singer’s sake.