Astral Codex Ten

Hans Jonas

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Hans Jonas

Article

Hans Jonas is a recurring person in the Astral Codex Ten archive, appearing 3 times across 3 issues between April 12, 2023 and July 31, 2025. The archive places it in contexts such as “they finally tapped Hans Jonas, a philosopher of Gnosticism”; “The OHRP’s answer would make Hans Jonas proud”; “This isn’t quite Hans Jonas’ position”. It most often appears alongside IRB, IRB, Jonas.

Metadata

  • Category: People
  • Mention count: 3
  • Issue count: 3
  • First seen: April 12, 2023
  • Last seen: July 31, 2025

Appears In

Source Context

Recovered passages from the original issue text. When the raw archive preserved outbound links inside the source passage, they are listed directly under the quote.

Book Review: From Oversight To Overkill
April 12, 2023 · Original source
In the late 1960s and early 1970s, Beecher’s activism, Shannon’s CRCs, and the mounting level of Tuskegee-style scandals came together in a demand for the American Academy of Arts and Sciences to create some official ethics report. Most ethicists demurred to dirty their hands with something as worldly as medicine; after some searching, they finally tapped Hans Jonas, a philosopher of Gnosticism. In retrospect, of course bioethics derives from a religion that believes the material world is evil and death is the only escape. I’m barely even joking here:
OHRP read the article, investigated, and learned that Johns Hopkins IRB had exempted the study from the privacy restrictions. These restrictions were hard-to-interpret, but OHRP decided to take a maximalist approach. They stepped in, shut down the study, and said it could not restart until they got consent from every patient, doctor, and nurse involved, plus separate approval from each Michigan hospital’s IRB. This was impossible; even if all doctors and nurses unanimously consented, the patients were mostly unconscious, and the under-resourced Detroit hospitals didn’t have IRBs. The OHRP’s answer would make Hans Jonas proud - that’s not our problem, guess you have to cancel the study.
Highlights From The Comments On IRBs
April 17, 2023 · Original source
Finally, most of the surveys in question are just a series of basic psychology scales or tasks both the worker and average SSC reader are very familiar with. I suspect many of them are administered by students as practice rather than 'serious' research. As the other poster said, rejected HITs are just any task the requestor declines for any reason. A worker's acceptance rate is extremely important - one of the few pieces of advice Amazon seems to give requestors is to filter for 98% or 99% acceptance rate. It's probably pretty reasonable for surveys - if you can't get 99 out of 100 of those filled out acceptably (assuming good faith by the requestors), maybe you should be filtered. It's also worth noting that Amazon makes communication difficult, and that rejected HITs can only be reversed for like a month - after that, they're permanently on your record. It's also probably worth restating: if a worker goes below the high 90s, they'll have access to fewer tasks, likely from less reputable requestors, and they'll need to do 100 of these to offset every rejection. And the worker is at much greater risk of being dug deeper into that hole by requestors rejecting their work in bad faith with no recourse - part of why surveys are popular is because the IRB can bludgeon requestors into accountability. Most of the surveys in question are also are the crumbs that filter through the grasping pedipalps of the hordes of workers (and their scripts). If people are seriously using MTurk to monetize their time, they're likely looking for 'batch HITs' - the sort of thing where there's hundreds or thousands of tasks that can be quickly repeated (moderating images, 3 cents for a sentiment analysis, a couple quarters to outline a car in an image, etc.) Of course, this mana from heaven rarely lasts long, and the worker always takes a risk - 'if I do 100 of these, and this is an unscrupulous requestor, well - I better have ten thousand accepted HITs under my belt.' That's why workers are so protective of their acceptance rate. Back to surveys - again as the other poster replied, most of what the average MTurk worker will see is probably a psychology study questionnaire with a series of whatever common scales, attention checks, and other tricks the worker has probably seen at least dozens if not hundreds of times by now. They often pay Amazon's princely sum of about 10 cents per (expected) minute - based on the minimum wage in whatever benighted 00s year Amazon Mechanical Turk launched. Anecdotally, it also seems like a lot of these are from students - probably just practice research by someone who likely has less experience with the platform than the worker themselves. The problem the requestor has - at least as of ~2018 - is that there is a lot of fraud with foreign workers getting access to MTurk accounts and submitting totally garbo data, often very quickly. Based purely on a 'time to complete' metric, this is hard to distinguish from a legit worker who has filled out hundreds of these and is looking to maximize how many pennies they get for their minutes. It also wasn't uncommon for workers to 'cook' such a survey - letting it sit at the end screen before submitting - just to avoid getting pinged for finishing it quickly. As for how this all ties back into Institutional Review Boards - well, yeah, griping to the IRB is often the MTurk worker's only recourse. Amazon just doesn't care, and as I recall a lot of requestors don't even know workers can contact them - and as mentioned there's a narrow time window to discuss rejected HITs before they become permanent. On the other hand, in a lot of cases this is basically a reddit mob complaining that a student doling out dimes screwed up their understanding of MTurk's arcane inner workings, and that's in the case that the workers aren't actually trying to defraud them for said dimes. 5. Comments About Regulation, Liability, and Vetocracy CatCube writes: I think the fundamental problem is that you cannot separate the ability to make a decision from the ability to make a *wrong* decision. However, our society--pushed by the regulator/lawyer/journalist/administrator axis you discuss--tries to use detailed written rules to prevent wrong decisions from being made. But, because of the decision/wrong decision inseparability thing, the consequences are that nobody has the ability to make a decision. This is ultimately a political question. It's not wrong, precisely, or right either. It's a question of value tradeoffs. Any constraint you put on a course of action is necessarily something that you value more than the action, but this isn't something people like to admit or hear voiced aloud. If you say, "We want to make sure that no infrastructure project will drive a species to extinction", then you are saying that's more important than building infrastructure. Which can be a defensible decision! But if you keep adding stuff--we need to make sure we're not burdening certain races, we need to make sure we're getting input from each neighborhood nearby, etc.--you can eventually end up overconstraining the problem, where there turns out to be no viable path forward for a project. This is often a consequence of the detailed rules to prevent wrong decisions. But because we can't admit that we're valuing things more than building stuff (or doing medical research, I guess?), we as a society just end up sitting and stewing about how we seemingly can't do anything anymore. We need to either: 1) admit we're fine with crumbling infrastructure, so long as we don't have any environmental, social, etc., impacts; or 2) decide which of those are less important and streamline the rules, admitting that sometimes the people who are thus able to make a decision are going to screw it up and do stuff we ultimately won't like. Darwin on why safetyism expanded just as the neoliberals were trying to decrease government regulation: Without the excuse of 'we were following all of the very strict and explicit regulations, so the bad thing that happened was a freak accident and not our fault' to rely on, companies had to take safety and caution and liability limitation and PR management into their own hands in a much more serious way. And without the confidence in very strict and explicit regulations to limit the bad things companies might do, and without democratically-elected regulators as a means to bring complaint and affect change, we became much more focused on seeking remedy for corporate malfeasance by suing companies into oblivion and destroying them in the court of public opinion. Basically, government actually *can* do useful things, as it turns out. One of the useful things it can do is be a third party to a dispute between two people or entities, such as 'corporations' and 'citizens', and use it's power to legibly and credibly ensure cooperation by explicitly specifying what will be considered defection and then punishing it harshly. This actually allows the two parties, which might otherwise be in conflict, to trust each other much more and cooperate much better, because their incentives have been shifted by a third party to make defection more costly. Without government playing that role, you can fall back into bad equilibrium of distrust and warring, which in this case might look like a wary populace ready to sue and decry at the slightest excuse, and paranoid corporations going overboard on caution and PR to shield from that. Meadow Freckle writes: Why can’t you sue an IRB for killing people for blocking research? You can clearly at least sometimes activist them into changing course. But their behavior seems sue-worthy in these examples, and completely irresponsible. We have negligence laws in other areas. Is there an airtight legal case that they’re beyond suing, or is it just that nobody’s tried? I don’t know, and this seems like an important question. And Donald writes: Why do we need special rules for medicine? The law has rules about what dangerous activities people are allowed to consent to, for example in the context of dangerous sports or dangerous jobs. Criminal and civil trials in this context seem to be a fairly functional system. If Doctors do bad things, they can stand in the accused box in court and get charged with assault or murder, with the same standards applied as are applied to everyone else. If there need to be exceptions, they should be exceptions of the form "doctors have special permission to do X". I do want to slightly defend something IRB-like here. When a doctor asks you to be part of a study, they’re implicitly promising that they did their homework, this is a valuable thing to study, and that there’s no obvious reason it should be extremely unsafe. As a patient (who may be uneducated) you have no way of knowing whether or not this promise is true. Every so often, someone does everything right, and something goes wrong anyway. A drug that everyone reasonably thought would be safe and effective turns out to have unpredictable side effects - this is part of why we have to do studies in the first place. If every time this happened, a doctor had to stand trial for assault/murder, nobody would ever study new drugs. Trials are a crapshoot, and juries tend to rule against doctors on the grounds that the disabled/dead patient is very sympathetic and everyone knows doctors/hospitals are rich and can give them infinite money as damages. There is no way for an average uneducated jury to distinguish between “doctor did their homework and got unlucky” and “doctor did an idiotic thing”. Either way, the prosecution can find “expert witnesses” to testify, for money, that you were an idiot and should have known the study would fail. In order to remove this risk, you need some standards for when a study is safe, so that if people sue you, you can say “I was following the standards and everyone else agreed with me that this was good” and then the lawsuit will fail. Right now those standards are “complied with an IRB”. This book is arguing that the IRB’s standards are too high, but we can’t cut the IRB out entirely without some kind of profound reform of the very concept of lawsuits, and I don’t know what that reform would look like. 6. Comments About The Act/Omission Distinction jumpingjacksplash writes: I think you've unintentionally elided two distinct points: first, that IRBs are wildly inefficient and often pointless within the prevailing legal-moral normative system (PLMNS); second, that IRBs are at odds with utilitarianism. Law in Anglo-Saxon countries, and most people's opinions, draw a huge distinction between harming someone and not helping them. If I cut you with a knife causing a small amount of blood loss and maybe a small scar, that's a serious crime because I have an obligation not to harm you. If I see a car hurtling towards you that you've got time to escape from if you notice it, but don't shout to warn you (even if I do this because I don't like you), then that's completely fine because I have no obligation to help you. This is the answer you'd get from both Christianity and Liberalism (in the old-fashioned/European sense of the term, cf. American Right-Libertarianism). Notably, in most Anglo-Saxon legal systems, you can't consent to be caused physical injury. Under PLMNS, researchers should always ask people if they consent to using their personal data in studies which are purely comparing data and don't change how someone will be treated. For anything that affects what medical treatment someone will or won't receive, you'd at least have to give them a full account of how their treatment would be different and what the risks of that are. If there's a real risk of killing someone, or permanently disabling them, you probably shouldn't be allowed to do the study even if all the participants give their informed consent. This isn't quite Hans Jonas' position, but it cashes out pretty similarly. That isn't to say the current IRB system works fine for PLMNS purposes; obviously there's a focus on matters that are simply irrelevant to anything anyone could be rationally concerned with. But if, for example, they were putting people on a different ventilator setting than they otherwise would, and that risked killing the patient, then that probably shouldn't be allowed; the fact that it might lead to the future survival of other, unconnected people isn't a relevant consideration, and nor is "the same number of people end up on each ventilator setting, who cares which ones it is" because under PLMNS individuals aren't fungible. Under utilitarianism, you'd probably still want some sort of oversight to eliminate pointless yet harmful experiments or reduce unnecessary harm, but it's not clear why subjects' consent would ever be a relevant concern; you might not want to tell them about the worst risks of a study, as this would upset them. The threshold would be really low, because any advance in medical science could potentially last for centuries and save vastly more people than the study would ever involve. The problem is, as is always the case for utilitarianism, this binds you to some pretty nasty stuff; I can't work out whether the Tuskegee experiment's findings have saved any lives, but Mengele's research has definitely saved more people than he killed, and I'd be surprised if that didn't apply to Unit 731 as well. The utilitarian IRB would presumably sign off on those. More interestingly, it might have to object to a study where everyone gives informed consent but the risk of serious harm to subjects is pretty high, and insist that it be done on people whose quality of life will be less affected if it goes wrong (or whose lower expected utility in the longer term makes their deaths less bad) such as prisoners or the disabled. The starting point to any ideal system has to be setting out what it's trying to achieve. Granted, if you wanted reform in the utilitarian direction, you probably wouldn't advocate a fully utilitarian system due to the tendency of the general public to recoil in horror. I want to stress how far we are away from “do experiments without patient’s consent” here - a much more common problem is that patients really want to be in experiments, and the system won’t allow it. This is most classic in studies on cancer, where patients really want access to experimental drugs and IRBs are constantly coming up with reasons not to give it to them. Jonas argued that all cancer studies should be banned because it’s impossible to consent when you’re desperate to survive, which isn’t the direction I would have taken that particular example in. But there are other examples - during COVID, lots of effective altruists stepped up to be in human challenge trials that would have gotten the vaccines tested faster, but the government wouldn’t allow them to participate. I would honestly be happy with a system that counts the harm of denying a patient’s ability to consent to an experiment they really want to be in as a negative, forget about any lives saved. And JDK writes: I haven't finished reading by felt compelled to comment on this: "the stricter IRB system in place since the '90s probably only prevents a single-digit number of deaths per decade, but causes tens of thousands more by preventing lifesaving studies." No. It does NOT "cause" deaths. We can't go down this weird path of imprecision about what "causing" means. I've been examining Ivan Illich, "Medical Nemesis" recently. By claiming IRBs which stop research ostensibly CAUSE death strikes me as cultural iatrogenesis masquerading as a cure for clinical iatrogenesis. […] "Might have been saved if" is not the same as "death was caused by". This seems to me to be a weird and overly metaphysical nitpick. Suppose a surgeon is operating on someone. In the process, they must clamp a blood vessel - this is completely safe for one minute, but if they leave it clamped more than one minute, the patient dies. They clamp it as usual, but I rush into the operating room and forceably restrain the surgeon and all the staff. The surgeon is unable to remove the clamp and the patient dies. I (and probably the legal system) would like to be able to say I caused the patient’s death in this scenario. But it sounds like JDK is saying I have to say the surgeon caused the patient's death and I was only tangentially involved. Here’s another example; suppose the US government bans all food production - farmers, hunters, fishermen, etc are forbidden from doing their jobs. After a few months, everyone starves to death. I might want to say something like “the US government’s ban on food production killed people”. But by JDK’s reasoning, this is wrong - the government merely prevented farmers and fishermen from saving people (by giving them food so they didn’t starve). I might want to say something like “Mao’s collective farming policy killed lots of people”. But since this is just a weaker version of hypothetical-Biden’s ban on food, by JDK’s reasoning I can’t do this. This seems contrary to common usage, common sense, and communicating information clearly. I have never heard any philosopher or dictionary suggest this, so what exactly is the argument? (JDK has a response here, but I didn’t find it especially enlightening) 7. Comments About The Applications For AI Metaphysiocrat writes: People have joked about applying NEPA review to AI capabilities research, but I wonder if some kind of IRB model might have legs (as part of a larger package of capabilities-slowing policy.) It’s embedded in research bureaucracies, we sort of know how to subject institutions to it, and so on. I can think of seven obvious reasons this wouldn’t work, but at this point I’m getting doomery enough that I feel like we may just have to throw every snowball we have at the train on the off chance one has stopping power. Zach Stein-Perlman writes: A colleague of mine is interested in 'IRBs for AI'-- he hasn't investigated it but has thought about IRB-y stuff in the context of takeaways for AI (https://wiki.aiimpacts.org/doku.php?id=responses_to_ai:technological_inevitability:incentivized_technologies_not_pursued:vaccine_challenge_trials). He's interested in people's takes on the topic. My take: my understanding is that the US can’t technically demand all doctors use IRBs. (Almost) al doctors use IRBs for a combination of a few reasons : The US government demands that everyone who receives federal funding use an IRB, and most doctors get some federal funding.
Inline links: writes, Darwin, writes, writes, writes, writes, has a response here, writes, writes, https://wiki.aiimpacts.org/doku.php?id=responses_to_ai:technological_inevitability:incentivized_technologies_not_pursued:vaccine_challenge_trials
Suddenly, Trait-Based Embryo Selection
July 31, 2025 · Original source
Aside from two bright orange squares (gallstones vs. hypertension and hypothyroidism - I don’t know what’s up with this and it doesn’t seem to be a widely-appreciated result) we see that most correlations are zero or positive - that is, selecting against one disease selects against another or at worst does nothing. In this ocean of blue, worrying about those few orange squares feels a bit motivated. Hans Jonas-ism says that no medical intervention may ever cause any harm, no matter how much benefit it produces. By this standard, perhaps slightly raising the risk of gallstones in the process of preventing various cancers and psychoses and other forms of human misery is unacceptable. To anyone with the more normal perspective where something with large benefits and tiny downsides is still pretty good, I don’t think the antagonistic pleiotropy argument carries much weight. Ethical Objection: Cost No way around this one: if these products work, they mean that rich people can have healthier/smarter/taller/prettier kids than poor people. One might object that at least they’re in good company: other products which help rich kids get healthier/smarter/taller/prettier than poor kids include private tutors, gyms, hair salons, health insurance, clothing, books, and food. Is this really the time to declare ourselves against this kind of thing? But maybe we should fight against expanding this already-bloated category. Or maybe there’s something more final about a genetic advantage. Maybe a stronger argument is that rich people get first crack at every new technology, but poor people usually follow close behind. The first cellphone, in 1982, cost $12,000 in today’s dollars. Now you can get something a thousand times better for $50, and Kenyan pastoralists use cell phones to call up the local shaman. The trajectory of genetics has been even more striking: sequencing a single genome cost about $100 million in 2000 and is somewhere around $100 today. Polygenic embryo selection has the potential to follow a similar path. There are two associated costs - sequencing the embryos, and running the analysis. Sequencing costs are decreasing and may eventually be comparable to the sorts of genetic screening (for e.g. Down Syndrome) that most families get anyway. Analysis costs are mostly the one-time expense of inventing the predictor; we might expect these to follow the same pattern as generic medications, where cutting-edge technology is jealously guarded and expensive, but last decade’s technology has made its way off patent and is cheap-to-free. A few groups have already created free open-source predictors; so far these are much worse than the private companies’ versions, but one of last year’s ACX Grantees is working on a better one. Also, it would be crazy for any forward-thinking government not to cover this; it could save hundreds of thousands of dollars in future health care expenses. In countries with public health care, this comes directly out of the government treasury; even in the US, it’s covered by Medicare after age 65. The government should be begging people to select embryos. The most persistent cost barrier is likely to be in vitro fertilization itself, a necessary precursor. In the US, 2-3% of babies are born through IVF. For those kids, this is a no-brainer - even if the cost never comes down, the cheaper products are only a fraction of total IVF expense. What about the other 98%? If those parents feel like they have to get embryo selection (and therefore IVF) to keep up, this could be a significant burden. IVF isn’t fun - it requires pumping a woman full of mind-altering hormones for weeks, extracting eggs in a minor surgery, and then implanting embryos in another minor surgery, all with a decent chance that some step will fail and you’ll have to do it all again. It also costs $15,000 in the US (less in poorer countries), and unlike the genetics, the cost has barely gone down in the past twenty-five years. Some countries, including Israel, offer free IVF for anybody who wants it. And universal basic IVF is surprisingly popular even in the usually government-phobic United States - Donald Trump made it part of his campaign platform. So there’s a plausible path to embryo selection for everyone who wants it. But it’s still going to take a while, it will hit different people at different times, and so far11 there’s no way around the month or two of various miserable medical procedures for women. Ethical Objection: Personhood Is it really correct to say that you have reduced someone’s risk of breast cancer by 46%, if what you’ve really done is closer to replacing them with a different person who is 46% less likely to have breast cancer? I cover this one in more depth here. Ethical Objection: Race This one is awkward: right now the technology works best for white people. Most genetic data available for research/commercial use comes from the UK, US, and Europe - areas which are mostly white. Asian biobanks, and those serving US minority communities, have been more reluctant to share data. So we know a lot about the genetics of white people, and only a limited amount about the genetics of anyone else. Companies are suitably embarrassed about this, and researchers in the field are working hard to wring every ounce of information out of the minority data they have. But for now, white people are the clear winner. Here’s data from Herasight: A European family with five embryos and no family history can cut their diabetes risk by 47%, and an African family 29%, with everyone else in between. As usual, all companies say that they adjust their scores based on the couple’s genetic ancestry. As usual, Herasight challenges them to publicly release data on exactly how they performed the adjustments and how well they work. All companies say they are working as hard as they can to improve cross-ancestry portability, but that progress will remain limited until governments collect/release better genetic data on non-white populations. Ethical Objection: Selection At some point, you’ve got to choose. Genomic Prediction and Herasight offer scores that aggregate overall health risks. Some people will follow them slavishly. Other people will try to second-guess them - would you prefer your child have lower cancer risk, or less chance of heart attacks? And this is the best case scenario! Herasight offers predictors for IQ, height and BMI; Nucleus offers those plus eye color and hair color12. A parent might encounter a situation where the embryo with their favorite eye color also has the highest cancer and schizophrenia risk, and choose to doom their child to cancer and schizophrenia because they really want pretty eyes. On average, even if everyone in the world selected for eye color, it wouldn’t raise cancer and schizophrenia risk. No not-deliberately-perverse polygenic selection choice can make your child worse off in expectation. Still, suppose you got cancer, and your mom admitted that she selected you for pretty eyes and didn’t even check the cancer column of the embryo selection report. How would you feel? And would you feel better or worse than someone whose parents didn’t do embryo selection at all, and spent the money on a Caribbean vacation? What if they selected your brother for everything great, then had you naturally? What if they selected you for IQ, but actually you are very stupid, and you were one of the 20% of cases where a predictor that’s right 80% of the time gets it wrong? Mark my words, one day there will be entire subfields of therapy dedicated to these issues. Going Nuclear Even as outsiders criticize the whole field, Herasight has launched a full-scale attack on competitor Nucleus. Herasight’s white paper compares its own predictors (favorably) to those of Orchid and Genomic Prediction… …but refuses to acknowledge Nucleus at all. In a supplementary note, the authors explain why: they accuse Nucleus of being so bad that it would “not yield a reliable or meaningful addition to our analysis”. They say Nucleus has inflated the accuracy of their scores. This is most dramatic for a few conditions like ADHD, where the leading published polygenic score is based on 2,300,000 variants but explains only ~1% of variance in the condition. Nucleus’ score is based on 12 variants13 and (implicitly) claims to explain 3-6%. This doesn’t make sense. Some of Nucleus’ other scores do use millions of variants. But many of these are 5-10 year old scores downloaded from open-source catalogs, whose accuracy statistics are easily available and far less than Nucleus claims. Here is what Herasight finds when they double-check Nucleus’ numbers: On their Substack, Herasight also criticizes Nucleus’ monogenic screening product. They point out cases where it fails to properly screen for the conditions it claims. For example, the Nucleus website advertises screening for spinal muscular atrophy: But on their gene list… …they don’t screen for SMN, which causes 95% of spinal muscular atrophy cases. They only screen for UBA1, which causes a distinct and much rarer condition called x-linked infantile spinal muscular atrophy. Professional organizations publish guidelines for what genes need to be screened in a screening product, and Nucleus does not appear to be following them. In further discussion, Herasight continued with exhaustive criticism of essentially everything Nucleus had ever done down to the smallest detail. Nucleus reports list the same baseline disease risk regardless of patient ancestry, but different ancestry groups should have different risks14. Nucleus’ physician reports sometimes list lower-than-average risk for patients with positive polygenic scores15. Nucleus’ age-based risk tables don’t distinguish between age and cohort effects (is this bad? see footnote16). My favorite critique is that Nucleus wrote a blog post criticizing competing company Orchid… …which included a section on how Orchid is a polygenic selection company, and polygenic selection companies are inherently “sketchy” and “honestly should be illegal”. But Nucleus is also a polygenic selection company! This is like Marlboro attacking Camel on the grounds that cigarettes are addictive and should be banned! Obviously something went wrong here - my guess is AI - and it’s a really bad look, especially when these scientific issues are so hard to litigate, and so many of us will have to go off gestalt impressions of corporate culture. Nucleus states that they validate their models internally and intend to make their results public soon. A Foothill Of The Future It’s hard not to love this technology. Lots of people (and the aforementioned professional organizations) manage anyway, but it’s hard. If this were a single-use medical treatment, delivered by a doctor after someone got the relevant condition, it would be one of the biggest advances of the decade - imagine a drug that cures 10 - 40%17 of breast cancers with no side effects! But in fact, it works for breast cancer, and schizophrenia, and heart attacks, and approximately everything else. The only things comparable are antibiotics and GLP-1RAs. And then there’s the IQ effects. Even after studying the literature, people have wildly different opinions about the importance of IQ. One of the most important debates is to what degree IQ differences are a cause of poverty, a consequence of poverty, or both. I lean towards both - a country with limited access to schools and medical care will have low average IQ, but as a consequence it probably won’t become the next big semiconductor hub. This technology could close half the IQ gap between poor and middle-income countries, or between middle-income and rich. Or it could give rich countries average IQs that have never been seen before, and let us see what kind of O-ring technologies (and new forms of social cooperation) lie just beyond the frontier. (this is the nice quantifiable argument in favor of IQ enhancement, but I find myself more convinced by fuzzier things - how much is it worth to be able to enjoy great art and literature? To fully comprehend what we know of nature, and be able to fully appreciate the mystery of the rest? To have a sense of why society works the way it does, instead of feeling like you’re being blown back and forth by institutions you don’t really understand? Amateur psychoanalysts like to say that the only people who care about IQ are those looking for an excuse to boast about how high their own is, but my experience is the opposite: I care about IQ because I bang up against the limits of my own a thousand times a day, and I hate it. I fantasize about ways to make my children smarter than I am for the same reason a dog confined in a tiny crate might fantasize about getting her puppies adopted out to a nice house with a big grassy yard.) My biggest qualm is that it might not matter. This is such a tiny foothill, flanking such a vast and foreboding range of mountains, that it might be a mistake to care about it at all. Selecting the best of five or ten embryos is not a very effective way to get the genes you want. There are things in the pipeline that will make this look like Hippocrates draining black bile. By the time the first polygenically selected children are adults, they’ll be old news. And then there’s AI. The average age at diagnosis for Type II diabetes is 45 years. Will there still be people growing gradually older and getting Type II diabetes and taking insulin injections in 2070? If not, what are we even doing here? Many people in the transhumanist community are still bullish on this technology. They think - well, there’s still an outside chance that something comes up and AGI takes another few decades. If we can enhance humans to be smarter, healthier, and more determined by the time it arrives, maybe we’ll have a better chance. Or maybe, if there’s a positive optimistic vision of a human-based high-tech future, people will be more willing to delay AI in the first place. I like this argument, but I also think it’s worth stepping back. What’s the point of anything? Why have kids at all in a world that’s changing this fast? Why save for the future? At some point your answer has to be romantic and aesthetic - it’s never been clear whether anything you do matters in any ultimate sense, but you’ve got to act as if it does and hope for the best. From that perspective, this is the most romantic technology of all. You’re not just giving a better life to your kids. Genes travel from generation to generation; you’re giving a better life your grandkids, your great-grandkids and so on to the point 1.77*log₂(population) generations from now when you are the ancestor of everybody and nobody. Somebody in Macaronesia in 3525 AD will avoid getting breast cancer because of you (if there is still cancer; if there are still breasts). Some combination of reasonable cost-benefit analysis and romantic/aesthetic commitments makes me want to have children despite the uncertainty, and the same combination made me sign up to use this technology despite the same. More later on how that’s going. 1I’m slightly mixing up two different things here - Down Syndrome can be detected with an aneuploidy test, but cystic fibrosis takes a more involved PGT-M test. 2There are two separate questions here. First, how much would diabetes risk decline if you selected the embryo with the lowest risk for diabetes - something you have no reason to do, since you have no reason to privilege diabetes risk over risk of any other disease? Second, how much would diabetes risk go down if you selected the embryo with the lowest health risk overall? Genomic Prediction’s their risk calculator calculator shows, seemingly paradoxically, that you get -38% relative risk by selecting against diabetes alone, but -41% relative risk by selecting against everything at once. Over email, they stand by this surprising result, saying that “for a couple of diseases (type II diabetes and CAD), the EHS actually accomplishes a larger risk reduction than the individual predictors. The explanation is that the EHS takes into account multiple PRS of diseases with high comorbidity”. See eg Figure 3 here: …and the section of the post called “Antagonistic Pleiotropy” for more. However, this paradoxical benefit is only true for a few conditions like diabetes - for everything else, selecting on health index does better than you would naively think, but still does not decrease the risk of a given condition as much as selecting against that condition directly. 3That is, new mutations in that particular baby, as opposed to older mutations already present in the parents. 4Conflicts of interest: I have used Orchid’s and Herasight’s products on my own embryos (not the ones used to conceive my existing kids, but for a potential third child), employees of Genomic Prediction and Herasight have been extremely helpful in contributing expertise to ACX posts on genetics, and I might invest in this field at some point (though haven’t done so yet). This post started as Herasight asking me to write about their white paper, then spiraled out of control. There were some unexpected time pressures and the result is that I didn’t get a chance to run everything in Herasight’s white paper by their competitors as thoroughly as I would like. Although I talked to representatives of all four companies profiled here, I feel like this probably reflects Herasight’s perspective better than other companies’, and that this is a major flaw. If other companies have responses, I’ll publish them. Thanks to all companies involved for their assistance on this article. Finally, I am favorably disposed toward Herasight because of how I learned about them: a professor named Jonathan Anomaly got cancelled from Penn for being too gung-ho about genetic enhancement, and used his newfound freedom to join a very-early-stage Herasight, raise their ambitions, and sell everyone (including me) on the idea. I grew up on a diet of books and movies about mad scientists, and I’m a sucker for a story about a guy named Doctor Anomaly pursuing revenge against the small-minded fools who destroyed his career by creating a race of superbabies. 5The version of the tool I looked at said 5.9 points for five embryos, up to 9 points for twenty embryos. The version of the tool on their current said says 5.3 - 9, so they might have recalculated after I finalized this article. 6Used in quotation marks because these scores were fine for the predictive tasks they were applied for - they just weren’t finding genes that directly caused the outcome of interest. 7Conflict of interest notice: this table was originally unadjusted. A representative of Herasight claimed that this was unfair, because each company used slightly different reporting conventions, and offered to correct for this in a neutral way. I retraced their reasoning, confirmed that the correction did not especially benefit Herasight at the expense of other companies, and accepted the correction. The original unadjusted table is below: Herasight was insufficiently comfortable with Nucleus’ methodology to even be willing to posit a corrected value, so I left their self-reported value in gray. 8Zagorsky (2007) says an extra IQ point means $234-$616/year in higher salary. The midpoint of $425 equals $670 in today’s dollars; assuming a forty-year career, Nucleus’ +1 point estimate is worth $26,800 (vs. $9,249 Nucleus cost) and Herasight’s +6 point estimate is worth $160,800 (vs. $53,250 Herasight cost). 9As part of researching this article, I asked all four major companies about their within-family validation strategies. Here are some details: Genomic Prediction discusses their strategy in this paper. The results are complicated to interpret - the within-family numbers often have such wide error bars that they overlap with both the across-family numbers and with zero - but looking qualitatively it seems like most scores on average lose about 25% of their risk reduction ability (though averages might not be the right way to do this, and some might be much more affected than others). Their website reports unadjusted, not within-family validated numbers; GP says they say this clearly on their site (which is true), Herasight counters that they still present their numbers as applicable to embryo selection (which is also true). To get the most applicable-to-embryo-selection numbers, you might want to adjust GP’s stated numbers down somewhat; it’s hard to say exactly how much, but maybe 20 - 25%?
Inline links: Hans Jonas-ism, somewhere around $100 today., Donald Trump made it part of his campaign platform, 11, here, https://substackcdn.com/image/fetch/$s_!1Alk!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F1af69f39-f353-4aa6-acb9-d8c3b05c7bac_728x895.jpeg, 12, Herasight’s white paper, https://substackcdn.com/image/fetch/$s_!S7lY!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F738260ba-8fe2-4647-8ca2-eeb4d13e0fce_605x341.png, 13, https://substackcdn.com/image/fetch/$s_!u7YE!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F451c286b-c677-47af-8c07-f0d993a14384_612x345.png, their Substack, the Nucleus website, https://substackcdn.com/image/fetch/$s_!XmL4!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Ff77915b4-3b36-4908-8f9f-032b7cf865ff_562x432.png, https://substackcdn.com/image/fetch/$s_!bxjb!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F2df9ffe5-17a3-4448-9a20-e9b27ac9a519_1250x795.png, publish guidelines, 14, 15, 16, a blog post criticizing competing company Orchid, https://substackcdn.com/image/fetch/$s_!MZCB!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F2cf9cbf4-825b-4373-9052-80e43c36febf_718x1035.png, 17, GLP-1RAs, O-ring technologies, things in the pipeline, everybody, nobody, 1, 2, their risk calculator, everything, here, https://substackcdn.com/image/fetch/$s_!jtkY!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fd645c392-fed1-4f02-9a2e-878b8c7ef7f2_909x878.png, 3, 4, 5, 6, 7, https://substackcdn.com/image/fetch/$s_!Vimq!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fca0f1f15-268d-465a-a70f-b7f1173c6111_566x166.png, https://substackcdn.com/image/fetch/$s_!3B0A!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Faccc7a65-b142-4bf6-927d-53eb607d71ef_552x155.png, 8, 9