Pascalian Longevity: Why not?

Scott Alexander of SlateStarCodex / AstralCodexTen recently wrote Pascalian Medicine, in which he looks at various substances purported to improve covid outcomes, but which have relatively low amounts of evidence in their favor, likening administration of all of them to patients to a Pascal’s wager-type argument: if there is a small probability of a potential treatment helping with covid, and if it’s also very unlikely that this treatment is harmful, should we just give it to the patient regardless of if the quality of evidence is low and uncertain, as it would clearly have a positive expected outcome regardless?

The naive answer to this could simply be to attempt to calculate an expected value (note: I use the term expected value often here, but in some cases the terms hazard ratio, relative risk, or odds ratio would be more appropriate) for each treatment, and administer it if it’s positive. But there could be some unintended consequences of using this methodology over the entire set of potential treatments: we could end up suggesting treatments of 10 or 100+ pills for conditions, and apart from something just feeling off about this, it could magnify potential drug interactions, some treatments could oppose others directly, the financial cost could start to become prohibitive, and it could decrease patient confidence and have many other undesirable second-order effects.

Pascalian Longevity

There are many counter-arguments presented to the above concept which become less salient when the goal is changed from ‘find drug treatments to prescribe to all covid patients’ to ‘find personal health interventions that increase your own lifespan/longevity’.

I am fortunate enough that I am able to evaluate potential longevity interventions myself, pay for them myself, administer them myself, and review their potential effects on me myself. I might not do a perfect job of this – research is difficult, time-consuming, and lacking in rigor and quantity, and finding appropriate longevity biomarkers to quantitatively asses the effects of interventions is also difficult. But uncertainty is a given here, and that is why we incorporate it into our frameworks when deciding if something is worth doing or not by calculating an expected value. Furthermore, any harm that I may accidentally incur will only be done to myself, reducing the ethical qualms of this framework to near-zero (I would strongly oppose arguments that I should not have the right to take drugs which I think may significantly improve my own health, although some may disagree here).

My modus operandi with respect to longevity may have many uncertainties in its output, but still operates with a very strong (in my opinion) positive expected value: If a substance significantly and consistently increases the lifespan of organisms similar to humans (ideally in humans), and is also very safe in humans, then it is something that I want to take

This is how I operate personally with longevity, and it does result in me taking quite a few things (currently I’m at around 15). I do still try to minimize what I take as a meta-principle (for example, setting a minimum threshold of expected value that a substance must provide to warrant inclusion, rather than simply accepting any positive expected value) for a few reasons: firstly, to reduce potential drug interactions (which we do attempt to asses on a per-substance basis, rather than account for as an unknown, but unknowns are unfortunately a very large component of messing with biology regardless). Secondly, to keep my costs relatively sane, although I am not too worried about this as there are few ways to spend money more effectively than on trying to improve your health. Thirdly, to reduce the occurrence of interventions that may have the same or opposing mechanisms of action (taking two things with the same mechanism of action may be okay, but sometimes dose-response curves are less favorable, and taking >~2x of something will result in diminished or even negative returns). Lastly, to minimize potential secondary side-effects that could be cumulative over large classes of substances (for example, effects on the liver).

I don’t intend to promote any specific substances or interventions here as I don’t give medical advice, nor do I want anything specific to be the focus of this post, but I do want to remind us that just as we can calculate expected values in a utilitarian fashion and get effective altruism as a result, we can do the same for longevity interventions and get a very strong chance at notably increasing our lifespan/healthspan as a result. I do have a list of some of what I take here, but it is definitely not intended to promote anything specific to others.

Why Not?: Potential counter-arguments

Algernon’s Law

Algernon’s Law is sometimes brought up, suggesting that evolution has already put a lot of effort into optimizing our body, and thus we are unlikely to find improvements easily. But, as Gwern notes in the above link, there’s at least three potential ways around this reasoning: interventions may be complex (and/or too far away in the evolutionary plane) and could not have easily been found, they may be minor or only work in some individuals, or they may have a large trade-off involved and cause harm to reproductive fitness.

Although some areas of future longevity treatments may fall under exception one and be complex enough that evolution could not have found them, I would suggest that the majority of today’s potential treatments fall under exception three: evolution optimizes for reproductive fitness, not for longevity, and for this reason there are many interventions which will improve our longevity that it has not given to us already (this is part of why I am more optimistic about longevity interventions than I am about intelligence interventions/nootropics).

For an extreme example of this, it has been noted that castrated males often live longer, and that this is obviously something evolution would not be very interested in exploring. Although this has been found with median lifespan in male mice (maybe in females too?), there is also purported historical data on Korean eunuchs suggesting that they may have lived a full 14-19 years longer (there are definitely potential confounding variables and/or bad data here, but we don’t have RCTs on this in humans for obvious reasons..), and a more recent study in sheep that is also highly relevant: Castration delays epigenetic aging and feminizes DNA methylation at androgen-regulated loci, where epigenetic aging clocks that look at DNA methylation are used in castrated sheep. There are other traits that seem to improve longevity as well, for example decreased height. It seems quite plausible that there are a lot of trade-offs that optimize for strong reproductive fitness early in the lifespan of organisms, which end up costing the organism dearly in terms of longevity. These trade-offs may be involved in many areas such as testosterone, estrogen, growth hormone, IGF-1, caloric restriction, mtor activation, and many others.

Large error in estimating unknown risks

One other counter-argument here is often along the lines of “you are messing with things you don’t understand, and you could be hurting yourself but be unaware of this; the damage may also be difficult to notice, or perhaps only become noticeable at a much later time”

It is true that our understanding of biology is lacking, and therefore also that we are operating in highly uncertain environments. I would be open to evidence that suggests reasoning for why we may be systemically underestimating the unknown risks of longevity interventions, but given how strong the potential upside is, these would have to be some pretty terrible mistakes that are being made. It is often noted how curing cancer may only extend human lifespan by a few years, whereas a longevity improvement of 5% for everyone would provide much more value (and is also much easier to find in my opinion). One could make an argument here that even if I was doing something that notably increased my risk of e.g. cancer, if the expected lifespan increase of this intervention was as much as 1-5%, this could still be a huge net positive for my health! I don’t take approaches that are this extreme regardless, and I try to keep the risk side of my risk/reward ratio low independently of the level of potential reward in attempt to account for this uncertainty. I am also not aware of many interventions that seem to have very high numbers in both the numerator and denominator here, although I am pretty certain that they do exist; I don’t currently take anything that I think has notably detrimental side-effects for the time being.

Is it fair to call this approach Pascallian?

The original nature of Pascal’s wager is that of extreme probabilities resulting in positive expected values, but the numbers that we are operating with are nowhere near as extreme as they could be. It is probably not a good idea to take 10,000 supplements, each of which have a 0.1% chance of extending your lifespan by a year for many reasons (similarly, if 10,000 people that claimed to be God all offered me immortality for a small fee, I would hope to decline all of their offers unless sufficient evidence was provided by one).

As I’m not arguing in favor of taking hundreds or thousands of supplements in the hopes that I strike gold with a few of them, it may be worth noting that ‘Pascallian Longevity’ would be a poor label for my strategy. Regardless, taking just 5-10 longevity interventions with a strong upside potential seems to be significantly more than almost everyone is doing already, so I still stand by my claim that there are many free lunches (free banquets, if you ask me) in this area, and I am very optimistic about the types of longevity interventions we’ll find in the coming decades.

Open to any corrections/comments on Twitter or any medium on my about page

My Favorite Links

This page contains a collection of some of my favorite links (mostly blog posts), roughly categorized by author. My hope is that others similar to myself can waste enjoy countless hours of reading from recursively following some of the links here. I haven’t yet finished this post but have published it regardless.

Current Substack subscriptions:

Scott Alexander (Twitter): As the author behind SlateStarCodex (now AstralCodexTen) and many great LessWrong posts, in my opinion Scott is among one of the best written content creators of the last decade. He focuses primarily on psychiatry, rationality, meta-science, critical thinking, and logical reasoning. Favorite posts:

  • todo

Gwern Branwen (Twitter – currently private): Well-known for having quality deep dives in diverse areas such as statistics, technology, machine learning, genetics, psychology, and many others. Also often recognized as an amazingly aesthetic, verbose, and highly-usable website. Favorite posts:

Scott Aaronson: A theoretical computer scientist with a focus on quantum computing and complexity theory. Although his posts on quantum computational complexity theory research go over my head, I’ve enjoyed some great content from him in other categories. Favorites:

Matt Levine (Twitter): An ex-Goldman Bloomberg opinion columnist with some wonderfully insightful and hilarious posts (offered as a free biweekly newsletter!) on the happenings in our modern yet often-insane financial world. Posts are generally centered around current events and are best read as they come out. Some examples:

Nintil (Twitter): A wonderful blog by Jose Luis Ricón with a focus on longevity, economics, and meta-science. Favorite posts:

Patrick Collison (Twitter): The CEO and co-founder of Stripe, often with focuses involving meta-science, individual and societal productivity, and economics

  • Fast: Examples of people quickly accomplishing ambitious things together
  • Questions: A short list of interesting questions
  • Advice: Advice, particularly for young and ambitious individuals
  • Book Recommendations: A well-sized list of suggested reading

Sam Altman (Twitter): The CEO of OpenAI and former president of Y Combinator, his posts often focus on startups, artificial intelligence, productivity, and science. Favorites:

  • How to be Successful: Thirteen thoughts on how to achieve long-term successful outcomes: learn a lot, compound yourself, work hard, and be ambitious
  • Productivity: Various productivity tips, such as ‘Picking the right thing to work on is the most important element of productivity and usually almost ignored. So think about it more!’
  • Advice for Ambitious 19 Year Olds: Advice for young and ambitious individuals, such as ‘The best people always seem to be building stuff and hanging around smart people’
  • How to Invest In Startups: Advice about being a good startup investor
  • Super successful companies: Notes some salient commonalities between many very successful companies
  • The Strength of Being Misunderstood: You should trade being short-term low-status for being long-term high-status

Paul Graham (Twitter): The founder of Y Combinator, with many posts focusing on startups, ideas and frameworks for everyday life, as well as advice and reflections for people that fit the founder/builder/nerd stereotype. Some favorites:

  • Do Things That Don’t Scale: An amazing tip on gaining initial traction and leverage by doing high-impact activities that won’t scale, but that will work effectively for the time being
  • What You Can’t Say: Reflections on that which exists outside of the Overton window
  • How to Make Wealth: An essay on effectively building wealth over time
  • Keep Your Identity Small: On why politics and religion yield such uniquely useless discussions due to excessive involvement with personal identity
  • Having Kids: Personal experiences and thoughts on having kids
  • It’s Charisma, Stupid: A 2004 essay arguing that charisma is the most important trait for elected politicians, using the US presidency as an example
  • What I worked an: A personal and emotional memoir on pg’s professional and personal history

Alexey Guzey (Twitter): Currently working on New Science, Alexey has some great blog posts with a focus on properly using the Internet for social leverage (reach out to people more, cold email people more, initiate conversations more, and create content more!), meta-science, productivity, biology, and more. Some favorites:

Melting Asphalt (Twitter): Written by Kevin Simler (along with Robin Hanson (Twitter), co-author of The Elephant in the Brain), Melting Asphalt has a wonderful collection of posts on evolutionary psychology, game theory, and novel and introspective takes on what makes us human. Favorites:

  • Neurons Gone Wild: A beautifully speculative post that suggests a recursively selfish model of biological neurons which enables selfish sub-agents and networks to co-exist in an evolutionary semi-competitive environment within our own minds. Probably my favorite post on this blog for several reasons. Also see Hallucinated Gods
  • Music in Human Evolution: A great book review of Why Do People Sing?: Music in Human Evolution by Joseph Jordania, involving predatory defense mechanisms, disposition of the dead, battle trances, and the audio-visual intimidation display
  • Crony Beliefs: On beliefs that stick around when they shouldn’t
  • Personality: The Body in Society:
    What is personality? ‘Nature and nurture work together to create a prototype, which then negotiates with the external world. The result is a strategy for getting along and getting ahead — a strategy we call “personality”, in other words, ‘Personality is a strategy for making the most of one’s particular lot in life.’ See also: part two and part three
  • Ads Don’t Work That Way: On ‘cultural imprinting’ and signaling in advertising
  • Doesn’t Matter, Warm Fuzzies: Discusses many interesting aspects of human ecology and society, with a focus on rituals, culture, confabulation, mimicry, and more
  • Social Status: Down the Rabbit Hole: On social status in humans, including an analysis of two proposed separate status systems: dominance/submission and prestige/admiration. See also: Social Status II: Cults and Loyalty
  • Border Stories: Borders are a necessary precondition for agency within a hostile ecosystem

Qualia Computing: With a subtitle of ‘revealing the computational properties of consciousness’, Qualia Computing is a great blog for anyone interested in the neurology, phenomenology, and interesting attempts at quantifications and explanations behind our own conscious experiences (qualia)

Patrick Mckenzie (Twitter): An entrepreneur and writer that lives in Japan and currently works at Stripe with a focus on startups and outreach, Patrick has many invaluable posts about finance, startups, marketing and professional communication, and highly-regarded SaaS and entrepreneurial advice. Favorite posts:

Fantastic Anachronism (Twitter): todo

Peter Attia (Twitter): todo

Vitalik Buterin (Twitter): todo

Nick Cammarata (Twitter): todo

Lesswrong: todo

Overcoming Bias: ‘This is a blog on why we believe and do what we do, why we pretend otherwise, how we might do better, and what our descendants might do, if they don’t all die’, from Robin Hanson.

Aella (Twitter): Popular Posts, Becoming A Whorelord: The Overly Analytical Guide To Escorting, Handling Accusations In Communities

Misc longevity sources

Misc vs/software sources

Misc meta-science sources

Misc rat-adj sources

Misc browser salient history grep sources

Wikipedia: todo

http://lukemuehlhauser.com/ https://marginalrevolution.com/?s=assorted+links https://lemire.me/blog/, dan luu, https://jakeseliger.com/tag/links/ https://thezvi.wordpress.com/about/

Miscellaneous: