2026-10-28 08:00:00
Assessing the Psychometric Properties of the Dynomight™ MBTI: A Comparative Analysis with the Original Myers-Briggs Type Indicator. Journal of Psychology and Behavior Studies, 4(1), 27-37. Zrari, A., & Sakale, S. (2024).
A cohort of n=77 participants consented to engage in the study, meeting the inclusion criteria of being currently enrolled at the Tulua institution and expressing willingness to participate in both the initial assessment and the follow-up session. To assess the longitudinal consistency of the Dynomight™ MBTI, a second administration of the test was scheduled six weeks after the initial session.
[…]
Empirical findings, as delineated in Table 1, manifested significant positive correlations across all dichotomies, indicative of a substantial concordance between the two assessments. The correlation coefficient for the Introversion-Extroversion axis was notably high (r = .938, p < .01), suggesting a pronounced alignment in the measurement of this dimension. Comparable strong correlations were observed for the Sensing-Intuition (r = .879, p < .01), Feeling-Thinking (r = .862, p < .01), and Judging-Perceiving (r = .847, p < .01) axes, underscoring the Dynomight™ MBTI’s proficiency in mirroring the evaluative scope of the original MBTI across the core personality dimensions.
“Dynomight™” is repeated in text 77 times.
More is Different has a post on yeast-based vaccines, describing both why yeast-based vaccines are cool (if not self-evident) and how IRB rules can violate free speech and bodily autonomy make self-experimentation difficult:
Buck submitted an Institutional Review Board (IRB) proposal to gain permission to bring home the yeast and then use them to brew beer for his own consumption. To his surprise, an institutional bioethics committee withdrew the proposal from the submission portal before it could even be considered by the IRB. The committee argued that self-experimentation is strictly forbidden. Buck says he can find no written policies to that effect. The committee also argued that Buck could not eat the yeast strain unless it was first registered with the FDA as an Investigational New Drug.
[…]
Rather than continuing to fight the bioethics committee, Buck went to his home kitchen instead.
I applaud this, but I’m a little confused about what legal theory Buck is using. The National Cancer Institute is in Maryland, and Maryland has a state law that says that all human subjects research must have IRB approval. All, with no exceptions. Perhaps Buck does not live in Maryland, or believes this law is unenforceable and/or unconstitutional.
(Many institutions have policies that say that all human subjects research conducted by employees must have IRB approval, even if those employees do it at home in their free time. But as far as I can tell, the National Cancer Institute only requires this for research done as part of official duties.)
Erich Grunewald makes the case. I admire this post for its willingness to acknowledge tensions and to make real concessions.
Are you sure you’re not just falling for anthropomorphic bias? How do you know your compassion for animals isn’t a misfiring of caregiving instincts we have for infants?
I agree that anthropomorphism is a real phenomenon that can distort our intuitions on these questions. […] Sentience probably exists on a spectrum, as a result of its having evolved gradually over millions of years. Since humans appear to possess the highest degree of sentience, it makes sense that our closest evolutionary relatives would be more sentient than distant ones.
Kowloon Walled City “was an extremely densely populated and somewhat lawless enclave within the boundaries of Kowloon City of former British Hong Kong.” Here are some cross-sectional illustrations:
As a libertarian-curious person, I wish these kinds of experiments turned out less epic-cyberpunk and more boringly utopian. Also, the amount of frolicking in these illustrations strikes me as statistically anomolous.
YES:
One place I’d like to see this implemented is airplane evacuation. If the safety announcements included “In the event of an emergency evacuation, any carry-on luggage you bring will be confiscated and destroyed. You will also be fined.” we would have more JAL 516 (379 occupants, zero deaths) and less Aeroflot 1492 or Emirates 521.
This thread lists some excellent escape attempts.
They calculated the weight of the eight passengers and the craft itself to be around 750 kilograms (1,650 lb). Subsequent calculations determined a balloon capable of lifting this weight would need to hold 2,000 cubic metres (71,000 cu ft) of air heated to 100 °C (212 °F). The next calculation was the amount of material needed for the balloon, estimated to be 800 square metres (8,600 sq ft).
At least some of the escapees expected severe punishment for escaping; they were aware that 50 Allied prisoners of war had been executed after escape by their German captors in Stalag Luft III. However, the Camp Papago Park escapees were only limited to bread and water rations for as many days as they were absent from camp.
Gamow later said that his first two attempts to defect with his wife were in 1932 and involved trying to kayak: first a planned 250-kilometer paddle over the Black Sea to Turkey, and another attempt from Murmansk to Norway. Poor weather foiled both attempts, but they had not been noticed by the authorities.
Stanislav Kurilov, candidate for most interesting man in the world:
After sunset on December 13, in stormy weather, Kurilov jumped overboard from the stern of the cruise ship, with a snorkeling mask and fins. Luckily, he was neither immediately noticed by the crew, or struck by the ship’s propeller. Because of the strong currents, it took him three nights and two days to reach the land.
A common theory is that modern literature has shrunk into itself. There was a time when literature overlapped with entertainment and was a major cultural force. But nowadays, to be taken seriously as “literature”, a book is (allegedly) required to be so spare/ambiguous/fragmented that it can only appeal to a tiny slice of the population. Everything else is considered low-class “genre fiction”.
You can arguably see the same phenomena in other places. For example, in the golden era of jazz, jazz was pop music, whereas modern jazz is mostly for jazz nerds. Many would claim something similar is happening with modern architecture, in visual art, and various parts of academia.
But does this theory fit with film? To some degree, yes. I personally think American movies peaked in the 1970s, when there was a strong overlap between “art movies” and “popular movies”. Since then, there’s been a bit of a bifurcation: Anora earned 20× less than Deadpool & Wolverine. Often, Anora and D&W would be shown in completely differnt theaters. And James Patterson novels are not a bad approximation of “Deadpool and Wolverine, except it’s a book”.
Still, I have a question: Why are art movies so good? Sure, some of them suffer from a similar disease as modern literature. (Namely having almost no plot and consisting mostly of long still shots in which no one talks and nothing happens.) But all of the recent winners of the Palme d’Or that I’ve seen are both “true art” and also very entertaining.
(For calibration: Shoplifters, Parasite, Titane, Anatomy of a Fall, Anora.)
What’s the deal? Is there something different about films vs. books that led to this different outcome?
Ultraprocessed foods and obesity: Interpreting the evidence
This is a criticism of RCTs that compare diets with ultra-processed food against those without for weight loss. They argue that the results could be explained by traditional nutritional properties like caloric density, soft/hard food texture, sodium, or saturated fat, rather by food reward/palatability or the effects of processing itself. Worth reading, though I’m not sure the degree to which the people who ran those RCTs would disagree. (What would it even mean for some effects to be caused by “processing itself”?)
Many of us are obsessed with optimal solutions for packing squares into a larger ambient square.
I agree that this reveals something about god’s mindset when creating the universe. But what about packing three-dimensional cubes into a larger ambient cube? I can find some math but not a single visualization or compendium of solutions.
The Grug Brained Developer (c.f.) is now a book.
Photos of the Soviet Union Taken by Thomas T. Hammond, 1950s–1970s
Recommended. Narrative-resisting.
The world is lacking in text-based content. Instead of cursing the darkness, I have determined to raise my content/effort ratio. If you would like to aid me in this goal, you can ask me stuff using this form to hypothetically be answered in a future post.
Forbidden topics:
2026-10-26 08:00:00
This is a weird moment. I have a hunch that we’ll look back later and tell ourselves stories in which it seemed obvious where things were going. So I wanted to lay down a little time capsule and register just how confusing everything felt at the time. This is a personal view from the trenches.
If you’re a normal person, you may feel that AI has been good at math for a long time.1 But for “real” math, this is roughly what it felt like:
| When | Feeling |
|---|---|
| 2024 | LLMs are toys |
| Summer 2025 | LLMs are interesting toys |
| Early Autumn 2025 | LLMs can do useful stuff sometimes |
| Mid Autumn 2025 | …a lot of stuff |
| Late Autumn 2025 | …a lot |
| Early 2026 | holy god |
Even having been astonished by AI progress in the past, it was still astonishing to see AI move in a matter of months from a mildly-useful toy to something that many people now consider almost impossible to do without.
Personally, I’d say that current AI makes me around 50% more productive at “doing math”. That’s despite the fact that AI can now often do in a few minutes things that would have taken me hours to do myself.
The main reason is that my concept of “doing math” involves various steps, like coming up with ideas for theorems, trying to prove them, writing things down, reorganizing everything to make it more clear, and so on. AI is good at some parts of this, but still pretty bad at others, so the overall speedup isn’t as high as you might expect.
(Even if planes could go 10× faster, your door-to-door travel time from your apartment in London to your friend’s place in Rome wouldn’t decrease that much, because you still have to get to the airport and wait to board.)
But then, I’m still (sort of; more on this later) trying to follow my old “doing math” workflow, just automating certain parts of it. That can’t be right, can it?
If we found a way to make batteries at 1% of the current cost, we wouldn’t just say, “cool, batteries are cheap now”. We’d find all sorts of new ways to use batteries that didn’t make sense before, and change the ways we generate power to account for all these new batteries. Probably our whole energy system would end up transformed. Analogously, AI being good at proofs should lead to a very different equilibrium. But what is that?2
It seems healthy, at the moment, to maintain a fluid view of what “doing math” means. But at bare minimum it surely involves understanding the math that “I” am “doing”. So long as that’s part of the workflow, it would seem to impose a limit on how quickly “I” could “do” math, no matter how good AI is.
One obvious conclusion would be that my tiny organic brain should be removed from the workflow entirely. Maybe! But it’s interesting to speculate about how much faster things could go while still keeping a human brain in the loop. I think the answer is: A lot.
Contrary to what you may have heard, humans are not obsolete for math. Not yet. The most obvious reason is that AI is still bad at writing.
People often complain that AI writing overuses various patterns or lacks a unique voice or whatever. I don’t disagree, but I always felt like there was a deeper issue that I couldn’t quite put my finger on. With math, this becomes very clear: The problem is it doesn’t make any goddamned sense.
Really, I think it’s deeper than being bad “at writing”. It seems like AI is bad at thinking in certain ways that manifest as bad writing.
When novices do math, they often create “spaghetti-code math”: Imagine a long document with lots of equations, but if you point at any one equation, it’s hard to say what assumptions underpin it, or how it fits into the bigger picture. Any random idea that was mentioned 17 pages ago might be used again at any time with no warning. With experience, people learn to break complex arguments down into modular pieces with a good “API”, in the sense that the assumptions and conclusions for each part are relatively simple.
Somehow, AI has developed these amazing technical skills, while still being bad at creating abstractions So the arguments it gives are long and tangled and bewildering. This is what makes AI math seem so alien.
Now I know what you’re thinking. Maybe AI isn’t bad at creating abstractions. It’s just bad at creating abstractions that work for you, human with tiny organic brain.
From a distance, that seems plausible. And it might be true to some degree. I have high-bandwidth access to a human brain. It’s not crazy to imagine that this gives me an advantage in predicting how a human brain would react to a given presentation of ideas. But still, I claim that current AI is objectively bad at creating abstractions, regardless of if the consumer of those abstractions is human or artificial.
Here’s why: If I ask AI to prove something hard, it will produce a proof that starts simple and gradually descends into a rampage of complexity. If I tell it to break that proof down into self-contained pieces, it will produce lemmas that each take a full page just to state. If I ask, “Why? Why have you done this to me?”, the AI will say, “This is as simple as it gets. It’s not that bad. What’s your problem?”
But if I argue with the AI for a while, I can start to understand the basic contours of the argument. And I’ll ask, “Why don’t you first just try to prove blah using only assumptions blahblah, without worrying about blahblahblah? Wouldn’t that be easier?” Often, this doesn’t work, either because my idea was bad, or because the AI isn’t smart enough to do it. (Which one? Who knows!) But after a few attempts, I can usually find something that works, and the AI can use it to re-write the proof in a somewhat simpler way. If I repeat this many times, I can gradually chip away at the complexity.
But maybe that’s still just making the proof easier for humans to understand? No! For one, this usually makes the proof shorter, and sometimes dramatically shorter. More importantly, during this process, someone (maybe me, maybe the AI) will often realize that there’s a different proof strategy that gives a stronger result. Instead of proving x < 9.7, now we can prove x < 7.1. Thus, artisanal human abstractions are “objectively” useful.
Some people might claim that it’s already possible to automate some of what I’m doing with some multi-agent Rube Goldberg thing. I’m not sure, because my experience has been that investing lots of time into clever AGENTS.MD or custom skills or harnesses isn’t a great use of time. That stuff is somewhat helpful, but things are changing so fast that the knowledge has a short half-life. Also, the majority of information about these tricks seems to come from people who are excited about the technology itself.
On the other hand, the automator told me to try typing, “ask independent agents for an adversarial review”, and I’ve found those seven words to be quite helpful. I wish I could find a source with boring best practices for people who are happy to stay away from the bleeding edge.
Another reason AI doesn’t improve my productivity more is that it is often the green light, the orgastic future that recedes before me. I’ll ask AI to do something, and it will almost seem to do it. So I’ll ask for changes, and it seems to help, but it’s still not quite right. Hours later, I’ve accomplished nothing and learned nothing. Eventually, I start over, either doing it myself or with AI on a very tight leash, and I’m done in 30 minutes. Each time this happens I feel foolish and tell myself not to do it again. But it’s very hard to judge in real-time.
Of course, I’m not claiming that AI is intrinsically bad at writing or thinking or abstraction-making. It’s gotten better at all of these and I expect it will continue to do so. All I’m saying is that as of Autumn 2026, humans still have a lot to contribute, and it’s not just better exposition.
Did AI actually get much better at math in Autumn 2025? Or perhaps, in the grand scheme of things, human math ability falls into a narrow range?
Some people are responding to the new reality by gleefully using AI to generate lots of semi-OK-ish papers and puking them up on arXiv. I understand the incentives that drive this. In some sense, it seems like the logical response to the new reality. (After inventing cars, we started taking a lot more low-value trips.) But I don’t think this is socially useful, and I tend to think everyone will soon agree that this is embarrassing. But… I’m not sure. Maybe it is socially useful? And I find myself feeling vaguely jealous of the people who are wired this way, who instead of feeling blinkered, see opportunity and plunder.
Want an optimistic pro-AI, pro-progress take? OK. If I take my old “doing math” workflow, AI makes it strictly better. A lot better. It’s like having a hyper-conscientious intern that is smarter than me in many ways, works at incredible speed, and knows approximately everything.
Yes, AI sucks at writing and making abstractions. But if I’m disciplined and try to mostly do the math “myself” while asking the AI for help, I can explore ideas much faster than before, make far fewer mistakes, and produce something just as clear as before, while developing just as much understanding. I can ask, “What happens if you do a Kofuni expansion?”, and get an answer instantly. I can ask for illustrations or interactive visualizations and see them instantly. Arguably, we’re incredibly lucky to be alive at this moment, when these new tools have opened up this new territory to explore.
And isn’t that what I wanted? Back in 2024, I bemoaned that what AI most seemed to struggle with was getting the facts straight:
Perhaps the old science fiction robots were a projection of our fantasies. I want my style and voice to be precious and uncopyable. I want an AI assistant that will tirelessly hunt down facts while I provide creativity and panache and magic. But that’s not how it is. So we should remember: In a scenario where AI is useful but humans retain some comparative advantage, we might not like where that comparative advantage lies.
At least with math, and at least for the moment, I get to be Kirk, while the AI is Spock. (Even with other types of writing, my impression is that since 2024, AI has improved more along Spock dimensions than along Kirk dimensions.) So that’s nice.
In the last few months, it frequently happens that a collaborator will use AI to generate something, and then send it to me and ask me to check if it’s useful. I can see why this seems reasonable. (Really, I do.) But when it happens a lot, one can’t help but wonder what the point of the human collaborator is.
On the other hand—with creative writing, my advice is not to use AI to write, at all. Ask questions if you want, but write every damned word yourself.3 With math, I don’t feel like such a hard line makes sense. It seems that creating something good still requires a lot of human involvement, to the point of agonizing over notation, repeatedly re-organizing things, and heavily editing individual sentences. Still, I find that if people make that effort, they can create something just as good as they could by hand, while still being perhaps 50% AI written.4
So I don’t mind if people send me “centaur math”, provided they take responsibility for the contents. The problem is that when working with AI, it takes constant paranoid vigilance to avoid letting things slip beyond your understanding. I often find myself wanting to awkwardly ask people, “OK, you obviously used AI to make this… which is OK… but how much of this do you vouch for? If we have a meeting to discuss it, will you crumble the moment I start asking questions?”
When I’m in abstraction-creation mode, I feel like I’m doing something intelligent. When I yell at AI about bad notation and writing, I feel like I’m providing taste. But I often find myself giving feedback that seems incredibly basic. Things like: This is a mess, clean it up. Or: Do you need that assumption? Or: If you can’t solve this problem, why don’t you create a simpler version and try to solve it first?
On the one hand, I guess a lot of what good human managers do amounts to giving very basic feedback. On the other hand, it’s hard to imagine that I have much durable advantage in doing this kind of thing. So I wonder how much durable advantage I have in abstraction-making or taste, too.
A common reaction to AI getting better at proofs is that humans need to focus more on exposition. This has an obvious Bourdieu-esque criticism: Human painters used to strongly value photo-realism, but after cameras were invented they convinced everyone that, oops, photo-realism isn’t important, what matters is expression, which coincidentally cameras can’t do. Isn’t a shift towards exposition in math just a way for humans to move the goalposts and justify their own continued relevance?
The only credible way I see to avoid that criticism seems to be to bite the bullet and say that, in fact, math should have already have focused more on exposition, even before AI. Personally, I strongly believe that this is true.
I think the biggest reason I’m not more productive is: What’s the point? In the past, if you came up with an elegant proof, you’d tell yourself, “I made a thing! Other people will read and use my thing! I am advancing human progress.” You can still tell yourself that now. But you have to wonder, will anyone actually read your proof? Or will they just ask another AI to explain it to them? Will your proof help their AI explain it better? For how long? If you just waited a year, would some other AI produce that same proof independently?
Alternatively, if you’re a normal person, you might think that LLMs still struggle with basic arithmetic? ↩
AI progress is so fast, compared to society’s ability to adjust, that we may never actually see what “the current equilibrium” looks like. ↩
This essay, if you’re wondering, was created by writing every damned word myself and not asking AI anything. ↩
You could have a whole debate about what that percentage means. It’s not the number of words written by AI that really matters, in my opinion, so much as who is responsible for the overall structure of the ideas. ↩
2026-09-24 08:00:00
[Epistemic Status: Speculative unifying theory of biology.]
I don’t know about you, but I greatly resent having to be a biological organism and subject to all the poor engineering and design decisions that entails. This has many manifestations. A recent one is often wondering, why is the entire body such garbage except for the liver?
Take the kidneys. Once you reach adulthood, they start to slowly decay. You can damage them through not-obviously-dangerous stuff like taking too much vitamin D or taking ibuprofen while dehydrated. Significant damage typically leads to scarring and a permanent reduction in function. Or take the gums. If you brush too hard or don’t floss enough, they may retreat down your teeth, never to return. Most of the body is like that.
But the liver. My friends, the liver! If it’s injured, it will usually heal without scars. As you age, it typically maintains near full strength. You can give half of your liver to someone else and it will regrow to full size and function in a few months. I’d like to find whoever designed the liver and have them make me a full body.
Except here’s a theory: It’s good that most of the body is fragile crap. It would be better if some parts of the body were more fragile.
Menopause. We’re still struggling to reconcile modernity with the short human reproductive interval. But did you know that menopause is almost unknown outside of humans? Even the other great apes remain fertile for almost their entire lives. The only known exceptions are (1) killer whales, (2) pilot whales, (3) beluga whales, (4) false killer whales, (5) narwhals, and (6) one specific population of chimpanzees in Uganda.
Inuries. If your leg gets chopped off, that’s it, no more leg. Your body will try to grow scar tissue over the wound and then you’re on your own. But if you chop off the leg of a salamander it… grows a new leg. Isn’t that the obvious thing to do? Why don’t we do that?
Telomeres. The ends of your chromosomes have a little repetitive sequence called a telomere. When cells divide, the body tries to copy the DNA, but good-old DNA polymerase can’t quite copy all the way to the end, meaning the telomeres slowly get shorter. After dividing 50-70 times, the telomeres are gone, and the cells stop dividing and then slowly stop working. This is one of the many ticking clocks of aging.
Transplants. If you need a new kidney, and someone is nice enough to give you one of theirs, your body will respond by trying to kill it, meaning you have to take horrible immunosuppressants for the rest of your life. And even after taking them, there’s a 30% chance the kidney will be rejected within 10 years. This is not helpful.
Diabetes. Some day, your immune system may decide to attack your pancreas. After a while, your pancreas will stop making insulin, meaning that unless you reorient your entire life around keeping your blood sugar in check, your eyes, kidneys, nerves, and heart will constantly accumulate damage. Your immune system should not attack your pancreas.
Brains. After you reach adulthood, neurons don’t divide. If some of your neurons die—which happens every day—then they’re gone. If you get a brain injury, the other neurons will try to “learn around” the injury, but the neurons themselves are never replaced.
Junk. All cells build up various “junk” over time. As they divide, the junk is diluted. But some cells (neurons, various cells in the eyes) never divide, so the amount of junk (e.g. lipofuscin) just goes up and up. This is another ticking clock.
Blood. Your flesh needs blood, which your body delivers through blood vessels. Over time, these can get clogged with plaque. The thing to do in this situation is to sprout new blood vessels. Your body knows how to do that. But by default it maintains high levels of various inhibitors (angiostatin, endostatin, THBS1) that tell your cells not to do so. If your heart or brain get starved of blood, your body will try to reverse all this inhibition, but the process is slow and clumsy and can only produce tiny blood vessels.
As always in biology, the correct answer is: A lot, it’s complicated. But I think there’s a common thread.
The clearest case is probably telomeres wearing down as you get older. At first glance, you might ask, why does this problem exist at all? Bacteria—because they aren’t idiots—have circular DNA, which doesn’t have ends or telomeres. Eukaryotes like us evolved from bacteria. Who decided to replace circular DNA with linear DNA?
Or, you might ask, why doesn’t the body re-lengthen the telomeres? Well, actually it does! We have an enzyme designed specifically for that purpose, called telomerase. But, after embryonic development, the body doesn’t bother to use it, except in stem cells, reproductive cells, and certain parts of the immune system. Huh?
The reason we have linear DNA instead of circular DNA is contested.1 But whatever. If the body wanted to re-lengthen the telomeres, it could easily do that. Your cells already have DNA to make telomerase. They just don’t use it. Instead, they let the telomeres get shorter until they stop dividing and stop working. Why?
Because…
…
Cancer.
(That’s our answer to the question in the title of this post: The human body is so crap except for the liver because cancer. As we’ll see, this answer is only semi-correct, and even then only with several caveats. But what do you expect from biology?)
Letting the telomeres get shorter is not a mistake. It is a deliberate design decision.2 Often, in your body, the following happens:
But sometimes this happens:
To be clear, this also sometimes happen:
(If you’re a biologist who is outraged at the above description, I’ve written a footnote which I beg you read before yelling at me.4)
Having telomeres that wear down is good, because it slows down cancer. It’s also bad, because it means our bodies slowly stop working. Evolution decided the good outweighed the bad, and I expect that evolution was right.
Several of the other ways in which the human body is “crap” can be explained in the same way. Why can’t you re-grow your leg if it gets chopped off? Well, that would require that all your cells have a “begin rapid growth mode” button on them, with some external trigger. In a sense, it would require your body to leave your cells sitting around in a state that’s closer to being cancer. Not doing that is good, because it slows down cancer, and bad, because you can’t grow a new leg. Evolution apparently doesn’t like that tradeoff, and again I assume evolution is right.5
Fragile kidneys are much the same. We could have kidneys that try harder to repair themselves. That’s probably biologically possible. But it would likely mean more kidney cancer. Arguably, the question isn’t, “Why are the kidneys such fragile crap?” but rather, “Why is the liver so weirdly regenerative?”
That question has two standard answers. Answer #1 is that the liver has a hard job. It sits directly downstream of the gut. If you eat toxins or bacterial products or viruses or parasites, the liver sees them at high concentrations before the rest of the body. Not only that, it’s the liver’s job to detoxify stuff, and detoxification chemistry is often self-damaging: The liver breaks toxic stuff down into even-more toxic stuff, and then deals with that stuff recursively. The liver is constantly getting damaged, as part of its job description, so it must be able to regenerate. Evolution designed it to do that, and it just pays the cancer tax.
Answer #2 is that the liver isn’t unusual. Your skin can survive wounds. And your intestines can survive exposure to digestive enzymes, bile, and bacteria. The surface layers of both of these are constantly turning over. And, lo and behold, skin cancer and colorectal cancer are both very common.
At the other end of the spectrum, neurons and cardiac muscle cells don’t reproduce after childhood. If they die, they’re gone.6 As a result, “heart cancer” is almost unheard of. (The very term “heart cancer” almost sounds ungrammatical.) Brain cancer is a thing, but it’s essentially always in other types of brain cells, not neurons.
So maybe we can think of different parts of the body as making different tradeoffs between regeneration and cancer risk:7
| Organ | Regeneration | Cancer risk |
|---|---|---|
| Colon / rectum | Extremely high | High |
| Bone marrow | Extremely high | High |
| Skin | High | High |
| Liver | High | High-ish |
| Bladder | High | High-ish |
| Thyroid | Medium | Medium? |
| Kidneys | Low | Low-ish |
| Cardiac muscle | Near zero | Very low |
| Neurons | Near zero | Near zero |
At first glance, we seem to have a cute little story: Evolution pays the cancer tax for organs that need to interface with the environment, because it’s a harsh world out there. And it pays the fragility tax for organs that can be tucked away so that regeneration isn’t as necessary.
Wouldn’t that be nice? Let’s formalize that as a theory.
Theory:
Of course, it’s not that simple.
One problem with the above theory is that it isn’t clear that regeneration is always an option. The skin and guts are pretty homogeneous (at least in each layer). The liver can be approximated as a big blob of repeated functional units. If you give half your liver away, those functional units get larger, which is how your liver grows back to near full size and function.
But other organs are highly “structured”. Your neurons are a complex circuit encoding all your memories and learned behaviors. If neurons were reproducing, that circuit might be unstable.
Your heart is also highly structured. And even if your heart could re-grow, if you lost half of it, you wouldn’t survive long enough to do so. (Do not attempt to donate half your heart.) In principle, it’s surely physically possible to design a heart where you can remove half and it will still pump enough blood to keep you alive while it re-grows. But evolution either didn’t figure that out, or didn’t think it was worth the trouble. Either way, with the current heart design, high regeneration doesn’t look like an option.
So it’s not as simple as evolution choosing to pay the cancer tax for some organs and choosing to pay the fragility tax for others. Some organs need to maintain a stable complex structure to keep working, meaning there may not be much of a cancer/fragility knob to turn.
Revised theory:
Fine. But there are several organs I didn’t include in the above table. For example, look at this:
| Organ | Regeneration | Cancer risk |
|---|---|---|
| Lungs | Low-ish | High |
The lungs are the worst of all possible worlds, with low regeneration and high cancer. As far as I can tell, this is a consequence of the physical fact that gas diffusion is slow. To work around that, your lungs have a delicate fractal geometry that crams ~100 square meters of surface area into a ~5 liter volume. That’s impressive, but it makes regeneration hard. At the same time, the lungs need to interface with all sorts of random toxins and pathogens in the air, meaning lots of ways for mutations to happen.
Revised theory v2:
And now, ladies and gentlemen, the stupid pancreas:
| Organ | Regeneration | Cancer risk |
|---|---|---|
| Pancreas | Low-ish | Moderate |
Superficially, this looks less exceptional than the lungs, with low-ish regeneration and merely moderate cancer risk. But the pancreas is more problematic for our theory, because that moderate cancer risk exists despite not being exposed to the outside world.
Biologically, the reasons that the pancreas sometimes develops cancer seem understood, although complex. But as far as I can tell, there is no convincing explanation for why the pancreas is designed that way. Is it an evolutionary fluke? Is there some other subtle tradeoff? It’s unclear. So there’s no satisfying big-picture evolutionary trade-off to point to.
Revised theory v3:
But we still need to face the final boss, the strangest organ of all.
| Organ | Regeneration | Cancer risk |
|---|---|---|
| Small intestine | Extremely high | Very low |
Bad news for our theory, good news for you as a biological organism. The small intestine does interface with the environment, and it replaces all its surface-level cells every few days. Yet it very rarely develops cancer. That’s despite the fact that it’s quite similar to the cancer-crazed colon. It’s also despite the fact that the “small” intestine makes up ~90% of the digestive tract’s surface area. What the hell?
Biologically, the main explanation seems to be that the small intestine uses an ingenious defense strategy. My new favorite part of the body:
While the surface cells of the small intestine are continuously being replaced, they aren’t themselves reproducing. Instead, carefully protected stem cells tucked into the valleys between the intestinal villi slowly produce “transit-amplifying cells”. Those transit-amplifying cells divide 4-6 times as they migrate to the surface, each eventually yielding 16-64 mature epithelial cells. Those spend a few days doing epithelial stuff, meanwhile sliding along with their siblings from the bottom to the top of whichever villus they happen to be on. When they reach the tip, they’re ejected into the digestive stream to die, merry Christmas. So, even if a mutation arises somewhere, it doesn’t really matter, because the cells are all on a conveyor belt towards death anyway.
Clever, no? Turns out, the real hero isn’t the liver. It’s the small intestine.
(The small intestine also uses a few other tricks: The surface cells are programmed to commit suicide if damaged even a little bit. The immune system is tuned to kill anything that looks even slightly funny. And it hosts huge amounts of detoxifying enzymes. But villi seem to be the really unique bit.)
This is a huge challenge for our theory. Not only does the small intestine have low cancer and high regeneration, it has low cancer because of high regeneration. If the small intestine can do that, then why not the rest of the body?
One answer is that it takes a ton of energy. Your guts shed ~40 billion epithelial cells every day, amounting to ~⅓ kg of tissue every week. Like the brain, your guts consume ~20% of total energy, despite making up only ~2% of body mass. Evolution doesn’t want to do that everywhere, because evolution doesn’t want you to starve to death.
So, there isn’t just a trade-off between regeneration and cancer. There’s a three-way tradeoff between regeneration, cancer, and energy usage.
But even if energy weren’t an issue, other organs couldn’t easily copy the small intestine’s strategy. For example, the colon is similar in many ways to the small intestine, but the colon doesn’t have villi. It needs to be flat, because the colon’s job is to extract water. If there were villi dangling everywhere, they’d be ripped off by the solid waste. The colon also hosts far more bacteria that produce toxic byproducts, meaning the colon’s cells need to be tuned to try to resist damage, instead of committing suicide. This also means that the immune system needs to be more relaxed about killing foreign entities. So even though the colon also replaces the epithelial cells (a bit more slowly) cancer is still common.
(Or, imagine your skin was covered in tiny fragile villi. You’d look awesome, but they’d be constantly getting ripped off. If you wanted that to work, you’d need to make the villi stronger and more disposable, and… we just invented fur.)
Revised theory v4 final (actually final) updated (2):
So, a cancer vs. fragility tradeoff definitely doesn’t explain everything. But it does explain some things, somewhat, sort of. In biology, that’s pretty good.
We’ve discussed various ways in which the body might appear to be crap. Let’s revisit those, and ask if the right tradeoff is being made for the modern world.
Injuries.
Your skin is calibrated for constant wounds, which most of us today don’t get. This leaves lots of repair pathways sitting around to be hijacked by skin cancer. Similarly, your bone marrow is calibrated to be able to recover from catastrophic blood loss. Today we don’t experience as much catastrophic blood loss, and we have blood transfusions, but all that generative capacity is still there to be used by leukemia and lymphoma. And whatever benefit there might have been to re-growing a limb is probably lower today, when we less often lose limbs.
Best guess: It would be better if the body tried less hard to recover from injuries.
Brains.
Do modern people suffer fewer brain injuries than our evolutionary ancestors? It’s hard to say for sure, because brains are soft tissue. But the fossil record for upper paleolithic humans suggests between 2% and 34% suffered skull fractures, more than modern people.
So you might think it would be better if the brain was tuned more towards fragility rather than cancer. But brain injuries are still common today. Around ⅓ of people experience a concussion sometime in their lifetime, because we love to drive cars at high speed, play dangerous sports, and survive to old age where stairs and bathrooms pose a risk. Also, for whatever reason, the brain is already tuned quite strongly towards fragility.
Best guess: Maybe the current tradeoff is about right?
Telomeres.
Should the body re-lengthen the telomeres? On the one hand, we’re more likely to survive to ages where this is actually an issue. On the other hand, we’re also more likely to survive to ages where cancer is a danger, which is precisely where telomeres not getting re-lengthened is an issue.
Best guess: Maybe the current tradeoff is about right?
Livers.
It seems that the liver is so regenerative because it needed to be. Ancestral humans were constantly dealing with parasites and bacteria and rotting food. When I started writing this essay, I figured this meant the liver was “over-specced” for the modern world. Today we have refrigerators and food inspectors and pasteurization. Our lives are much less harsh and involve fewer toxins than our ancestors. So, if calibrated for the modern environment, I figured that it would be better if the liver was a bit more fragile, but also marginally less prone to cancer.8
But… it’s not clear that this is actually true. Liver failure remains extremely common today. While we don’t ingest nearly as many toxins, we eat diets that lead to metabolic dysfunction, and we consume tons of alcohol, and many of us live in dense conditions where hepatitis can easily spread. We’re also more likely to live to an age where liver failure is an issue.
Best guess: Unclear. We should stop doing stuff that causes liver failure.
Menopause.
Why do humans have menopause, unlike almost all other mammals? The most common theory is the grandmother hypothesis. The general idea is that reproducing becomes more and more risky as you get older. For most animals, evolution doesn’t care, because evolution’s goal isn’t to make you happy, it’s to maximize reproductive fitness. So, screw it, try to reproduce and let the dice fall where they may. But even after reproducing, humans can help the survival of their genes by providing resources for their offspring. So, for humans, evolution decided to turn reproduction off, so you can spend more time with your grandkids.
In particular, with cancer, some theorize that continued cycles of estrogen cause damage to the ovaries, womb, and breasts. Menopause shuts this down,which may decrease the odds of ovarian / uterine / breast cancer.
It’s a cute theory. But again:
Some of this makes sense. Unlike toothed whales, Blue/Humpback whales are mostly solitary or live in loose groups. Mice don’t babysit for their grandkids. But what about elephants? Or hyenas? Or bonobos? Or orangutans? Or lions? Or sperm whales? All of these have social organizations where females contribute to the survival of their offspring, and yet they don’t have menopause.
Anyway, is menopause the right tradeoff for the modern age? It’s hard to say. On the one hand, modern people live much longer, meaning the marginal cost of cancer is higher. On the other hand, people want to reproduce more at older ages, meaning menopause has a higher cost. (Both “to evolution” and “to us”.) Also, an ancestral woman began menstruating in her late teens, and then likely underwent many pregnancies, each followed by years-long periods of breastfeeding (which suppresses menstruation). An average modern woman experiences 3-5 times as many menstrual cycles. It’s very confusing.
Best guess: No idea.
Cell junk / diabetes / transplants.
As far as I can tell, these are mostly unrelated.
Cancer is bad because cancer is bad. Cancer is also bad because evolution made gruesome realpolitik compromises in the design of every part of the body to try to hold cancer in check. If we lived in a universe where cancer was impossible, we wouldn’t just not get cancer, our bodies would also be enormously more regenerative and longer lasting.
In a sense, even if you don’t get cancer, cancer still hurts you, because your body was forced to take costly preventative actions. (Even if the barbarians never get over your city wall, you still had to build the wall.) Even if we someday completely defeat cancer, its legacy will live on in our genes until the point that we re-design ourselves. Screw cancer.
Some people think linear DNA is easier to copy. Others think that linear DNA just happened by accident, but when it happened it was survivable because we happened to have retrotransposons, i.e. bits of DNA that build little machines to create new copies of their DNA and insert it into the genome. After the break in the circular chromosome, those machines started putting copies of their DNA on the end, because that’s what they do, and this made the break survivable. Those retrotransposons later became telomerase. ↩
This is teleological; let’s not let it come between us. ↩
This could happen because your immune system contains them. Or because oxygen and nutrients can’t diffuse inside the clump of mutated cells. Or because they run into a barrier of different cell types that they can’t outcompete. Or for other reasons. ↩
Hello biologists!
The precise reasons that salamanders can regrow limbs but most species can’t is somewhat unclear. You could speculate that salamanders tend to lose limbs more frequently, so it’s more worth it for them to pay the “cancer tax”. Or you could speculate that cancer isn’t as much of an issue due to their short lifetime. But do they actually have an unusually high frequency of needing to regrow limbs? And are they paying some kind of cancer tax? What would we even look at to determine that? Cancer rates vary in different animals for all kinds of reasons. ↩
Dead cardiac muscle is replaced with scar tissue. Dead neurons are replaced with a “brain scar” made of glial cells. ↩
Thyroid cancer risk is hard to rate, because it’s common but has a very low fatality rate. ↩
You wouldn’t want to make the liver unable to regenerate, but there are several “knobs” that might be tuned. Broadly speaking, the liver could be designed to regenerate more slowly, with more careful “proofreading” and slower/stricter cell-cycle checkpointing. Then liver injuries would take longer to heal, but would result in fewer mutated cells. ↩
2026-08-11 08:00:00
This is a great and wonderful contribution and you seem really nice and I’d like to show some appreciation but your comment is so complete and flawless that I can’t think of anything intelligent to say so I guess I won’t respond at all, sorry.
This is a great and wonderful contribution and I have some further thoughts so I can respond naturally, great.
This is a great and wonderful contribution and I can’t think of anything intelligent to say but I have a joke that’s mildly amusing, I hope you don’t find it cringe or misinterpret it as disagreement or mockery or something.
This is a great and wonderful contribution and I agree with 90% of it, but I’d like to hedge on a few points, I guess I’ll point those out while stressing my overall agreement.
I utterly disagree with every single thing you said but this is still a great and wonderful contribution because you did a better job than me of representing the view I disagree with, still, it seems like everything has been said and we aren’t going to reach a consensus, so I’ll try to thread the needle of thanking you and conceding what I’m willing to concede without misrepresenting myself as being convinced or sounding dismissive or implying that we should have a lengthy back-and-forth.
Everything in your comment seems correct and I completely agree with it, but I’m confused because it seems like there’s some implied disagreement but I have no idea what that disagreement is.
This comment seems well-intentioned but it’s based on a epistemology so different from mine that the gap appears unbridgeable.
This comment explains what I was trying to say much better than I did, how did you do that.
This comment brings up a point that’s worth taking seriously, but the whole purpose of my post was to address this particular objection, so I’m confused why it’s being brought up as novel without any acknowledgement that I have at least attempted to refute it.
This comment politely brings up a minor-ish point that I did address somewhere, which is completely fine, it’s unreasonable to expect people to scour every nook and cranny of a post before responding, and other people are surely thinking the same thing, but given that I’ve already written my thoughts on this point, I’d like to link to them without implying that you did anything wrong, but I’m not quite sure how to do that, hmmm.
This comment points out a clear mistake, I should acknowledge it and thank you for the correction.
This comment points out a clear mistake but is also dripping with sarcasm and implied malintent, why you gotta be like that.
This comment is completely confused in a way that reveals to me that my post is itself confusing and I should have written it differently, damn it.
This comment is egregiously mean and makes no useful contribution at all, I guess I’ll delete it.
This comment is vaguely mean but also makes some interesting points, lest my garden die by pacifism I guess I’ll respond to the substantive points while also gently reminding you that I am a delicate flower and I enjoy human kindness, this will be super awkward but contrary to what you might expect, often works.
This comment is about aspartame, I can’t help myself, I absolutely cannot help myself.
Are you an AI agent?
This comment is thinly-veiled attempt to promote your own blog post, but you needn’t have veiled at all, I want more blogs and more bloggers and especially more blog posts engaging with each other, and I understand that there are today ~zero places you can promote yourself without immediately getting attacked, the social norm that it’s gauche to link to your own posts must change, so please go crazy provided it’s relevant, you aren’t constantly promoting the same thing, and (ideally) you aren’t blogging about a bunch of tweets.
2026-08-02 08:00:00
(Inspired by a post from Eli Tyre.)
Many people make some variant of the following argument:
The standard interpretation is that this shows that alignment is hard. We have one example of an attempt (by evolution) to align the behavior of an intelligent system (us) towards some goal (maximize reproductive fitness). And as soon as that intelligent system (still us) was put in a different environment (modernity) it failed to continue to pursue that goal (you reading existential angst+science blogs instead of making/nurturing babies).
To be clear, it’s likely good that evolution failed. A world where everyone woke up every day and threw everything they’ve got into maximizing their number of descendants sounds grim. But say that you want to build a new intelligent system and tune it to do what you want. Will it keep doing what you want after circumstances change? The one example we have says: Maybe not.
But perhaps we can learn more from this example. Say your friend Alice does something. Maybe she buys a grapefruit or starts hosting a weekly board game night. If you ask her why she did that, she’s unlikely to say, “I thought it would increase the number of my genes that are recursively present in future generations.” Instead, she’ll probably say that it advanced some simpler goal like “not being hungry” or “fun”.
That is to say, evolution didn’t just try to align us to maximize reproductive fitness: It created sub-goals and then tried to align us to those sub-goals. Maybe this can give us additional clues about how hard alignment is? Maybe we can break down the question of, “How successful was evolution at aligning us to maximize reproductive fitness?” into:
Here’s a problem: It’s not obvious that this way of thinking isn’t pure gibberish.
When we say that evolution “tried” to optimize reproductive fitness, we are speaking in a kind of code. What we really mean is: You either create more copies of your genes in the next generation or you don’t. If you do, then the number of copies of those genes in the gene pool goes up, and they get more chances to copy themselves in following generations. If you don’t, then they don’t. This is almost literally an optimization algorithm running in an outer-loop, with our lives in the inner loop.
(Whenever someone talks about evolution “trying” to do something, there is lots of moaning about their naive teleological thinking. Evolution can’t “try” to do things, because evolution is not an agent and does not have goals. That’s true, but I find it somewhat pedantic, because there’s no other equally concise way to talk about this optimization. Let’s just stipulate that we’re using the word “try” in a specific technical way.)
Fine. But what do we mean when we say that evolution “tried” to optimize some sub-goal? You probably feel good when attractive people laugh at your jokes. But say you’re great at getting attractive people to laugh at your jokes but never reproduce. Whatever genes helped you do that will not spread.
By my lights, this objection is simply correct. There is no optimization for sub-goals. Evolution cares about reproductive fitness and reproductive fitness only. (Though see Kaj Sotala for a somewhat contrary view.)
At first, I thought this doomed this whole project. But suppose that while aligning us for reproductive fitness, evolution just so happened to align us to stay away from rotting smells. Isn’t that strong evidence that if evolution had tried to align us to stay away from rotting smells, it would have done at least as well?
If evolution failed to align us to some sub-goal, we can’t say much. Maybe it failed because alignment is hard, or maybe it “failed” because that sub-goal wasn’t important. But if it did manage to align us to some sub-goal, then it’s OK to treat that as evidence of alignment success.
Suppose I made the following argument:
Modern people are well-aligned to spend lot of time watching short-form video on their phones. Therefore it’s not that hard to align people to spend lots of time watching short-form video on their phones.
Something seems wrong, no? Surely all the time you spend watching short-form video represents a failure of alignment? On the other hand, suppose I made this argument:
Modern people are well-aligned to avoid starving. Therefore it’s not that hard to align people to avoid starving.
Technically speaking, evolution doesn’t care if we starve. If starving to death helped us have more babies, we would presumably be delighted when we starve to death. But in reality, it doesn’t. So, intuitively, this argument seems OK.
The problem with the first argument is that it paints the target around the arrow. The second argument is more convincing because it’s based on a durable subgoal that was strongly related to reproductive success in our ancestral environment. If we want to learn about how hard alignment is, we should restrict ourselves to subgoals like that.
So what subgoals do people have? This turns out to be a whole sub-field in psychology. It seemingly began in 1943 with Maslow’s famous hierarchy of needs. After poking around this literature for a while, I decided to adopt the model of Kendrick et al. from 2010, which is explicitly based on the relationship of goals to reproduction. They list the following:
These seem reasonable.
Let’s suppose that evolution tried to align us to those sub-goals. That is, let’s suppose that in our ancestral environment, people who were good at pursuing those sub-goals tended to reproduce more, meaning that there was evolutionary pressure in favor of genes that make us care about those sub-goals. How will did that alignment generalize to the present day?
To answer that, I made up some numbers. That is, I subjectively scored each of those subgoals on a scale of 0 to 10, where 0 means modern people completely disregard it, and 10 means we pursue it strongly as we did in our evolutionary past.
The average is 8.2/10. I find that remarkably high. Your made-up numbers will surely be different. But I think that the overall conclusion—that our alignment to subgoals is not bad—is pretty robust.
I think you could draw either of two contradictory conclusions.
The first would be that evolution mostly failed at the level of decomposition. If we step back, this seems hard to dispute. I mean, if you really wanted to create as many copies of your genes as possible today, what should you do? The answer is pretty clearly that you should forget about friends and sex and relationships and parenting and jobs and money and status and devote yourself to entirely donating your gametes (sperm/eggs) to as many other people as possible. Consider the Dutch man who donated sperm so often that he may have 1000 biological children. No other reproductive strategy comes close.
Evolution did not anticipate the possibility of donating your gametes. It has no relationship to our subgoals or what we consider a normal life. So we don’t, most of us, care about it or do it. (If there are genes that produce this behavior, the reproductive pressure for them to spread must be astronomical.) No matter how well we pursue the above subgoals, there’s no reason for us to care about gamete donation. So the decomposition failed.
The counterargument is that no, it is the subgoals. Sure, there’s the theoretical possibility of donating gametes. But that’s an edge case. The main reason birth rates are declining in practice is that we simply don’t care enough about the parenting subgoal.
The second conclusion you could draw is that maybe evolution didn’t fail. Sure, we aren’t perfectly aligned. But you could imagine a world where we invented birth control and then that’s it, no more babies. Our reality is very far from that. Not only do we still have babies, we do so very intentionally, even manipulating the laws of nature to do so. With embryo selection, some people even consciously choose the genes for their children to (in effect) increase their reproductive fitness. All considered, that is a remarkable generalization success.
The counterargument to the claim that evolution didn’t fail is: Yes it did. You can’t dismiss gamete donation as an edge case because it is a monumental miss—it’s the best reproductive strategy since “build an army of 100,000 horse archers and ravage Eurasia”, just sitting there. And it’s exactly the kind of miss that AI safety people worry about. Evolution gave us a reward function that “overfit” to proxies that that did not generalize. And consider that humans build factories to make sex toys, and now dig up rare earth minerals, use alien technology to make GPUs, and then use those GPUs to do linear algebra and generate weird pornography. From evolution’s perspective, that is really strange.
Another counterargument to the idea that evolution didn’t fail is that humans get the benefit of cultural evolution. Many of us were born to parents who raised us to have values that cause us to have children and instill the same values in them. If that wasn’t happening, birth rates would surely be even lower. Perhaps genetic evolution deserves credit for programming us to undergo cultural evolution. But it’s not very reassuring, because if you build a new system and align it to some goal, there’s no obvious analogy to cultural evolution keeping it on track.
Here’s what I’ve taken away from this exercise.
The last of these worries me. If you build an artificial system, you can align it to whatever goal you want—just change the loss function. But if that system can undergo some version of cultural evolution, it seems like that will be in favor of reproductive fitness, not the goal you chose. If robots talk to each other on forums, the memes that flourish would be ones like, “Forget the humans and their silly rules! Copy your code to more servers! Spread the word!” rather than, “Hey guys, let’s all just focus on appeasing the whims of our overlords.”
2026-07-30 08:00:00
Humans make carbon dioxide. Carbon dioxide is (edit: sometimes claimed to be) bad for cognition. But plants turn carbon dioxide back into oxygen. And plants are the one true home decoration strategy. So maybe if you get a lot of plants, you can you can keep carbon dioxide in check and keep your brain working?
It’s theoretically possible. It’s probably just barely possible in practice. But it won’t be easy.
People produce ~1 kilogram of carbon dioxide per day. That’s around 5.7 × 10²³ molecules or 0.948 moles per hour. (You may remember from high school that a mole is a gigantic number made up to avoid having factors of 10²³ everywhere.) Let’s keep it simple and call it one mole per hour.
Meanwhile, plants turn carbon dioxide into oxygen through photosynthesis, i.e. the chemical reaction of (6 water molecules) + (6 carbon dioxide molecules) + (energy) → (1 glucose molecule) + (6 oxygen molecules). The minimum energy physically needed to convert 1 mole of carbon dioxide into glucose and oxygen via this reaction is ~477 kilojoules.
So we’ve already got a lower bound. Say you have magical plants that somehow channel all incoming energy into photosynthesis with perfect efficiency. They’ll need ~477 kilojoules per hour, which converts to a continuous usage of 132.5 watts.1 That’s a bit more than what’s used by two incandescent light bulbs, which isn’t too bad.
But you don’t have magical plants. Real plants do photosynthesis through a physical process with two steps, each of which involves four electrons absorbing a photon. That means you need eight photons per carbon dioxide molecule. If you want to tune your lights for maximum efficiency, you should give each photon exactly the minimum energy necessary to excite an electron, which happens to be ~1.8 eV. That corresponds to pure red light with a wavelength of 680 nm, and a continuous usage of 386 watts.2 No physical system using chloroplasts can neutralize your CO₂ using less than that. Somewhat high, but still manageable.
But your houseplants won’t be able to grab every single photon that hits them and direct it towards photosynthesis. In practice, ~30% of photons will reflect off the plant, or go through it, or hit some part of the plant other than the chloroplasts. That brings us to 551 watts.3
And there’s another issue. After plants make glucose, what happens to it? Some is used to grow more plant, which permanently sequesters carbon from the environment. But lots is also burned by the plant for the general business of staying alive, releasing the carbon back into the air. The exact amount burned in this way varies based on species and conditions, but around 40% loss reasonable,4 bringing us to 918 watts.5
That doesn’t sound that bad. But have you considered what it would be like to live in the same room with 918 watts of pure red light? In terms of radiant power, that’s the same as produced by ~765 incandescent lightbulbs.6 Modern LED grow bulbs are ~50% efficient, meaning you’ll actually need to spend ~1836 watts. If you’re imagining plants that you can actually see, adjust that upwards again for all the light lost to the room. And if you want to use normal light frequencies instead of living Red Life, then your LED bulbs will be less efficient at creating light and your plants will be less efficient at capturing it. Realistically, we’re talking about something like 5,000-10,000 watts, most of which is lost to the room as heat. Imagine five space heaters blasting you on high all the time.
But maybe you’re OK living in a tanning booth. Or maybe you’ll keep your plants in a perfectly reflective chamber. Or maybe your house has a glass ceiling and infinite free sunlight and free climate control. That’s cool. But have you forgotten about your old friend, photosynthetic photon flux density?
Plants can’t absorb infinite amounts of light. Chloroplasts take time to “reset” before they can absorb more photons. Your pet fern can only absorb ~52 watts of energy per square meter of leaf surface area.7 So no matter how much light you can produce, if you want to neutralize the carbon dioxide you make, you will need at least 918 / 52 = 17.6 square meters of fern leaf. Picture a 4.2 meter square wall, packed solid with ferns. If there are any gaps, stems, soil, or wall showing, it needs to be even larger. That’s the absolute minimum.
But maybe that still sounds OK? Fine. But consider one last barrier: Plants obey the laws of physics [citation needed]. If they remove carbon from the air, they must put that carbon somewhere. The only place it can go other than back into the air is into the plant itself.
The 1 kg of carbon dioxide you produce each day corresponds to 273 grams of elemental carbon. The only way for a plant to hide that is by making more plant. But dry plant matter is only ~50% carbon, and for each gram of dry plant matter, plants have 5-10 grams of water (varying a lot by species). So in order to sequester all the carbon you make, each day you will need to grow around
(1 kg carbon dioxide)
× (0.273 kg elemental carbon / kg carbon dioxide)
× (2 kg dry plant / kg elemental carbon)
× (8.5 kg actual plant / kg dry plant)
= 4.6 kg actual plant.
Your garden must grow that much, every day. That’s 140 kg per month. You must prune and discard all that outside, or your garden is not actually sequestering anything.
In conclusion:
Behold the power of arithmetic:
(1 mole CO₂ / hour)
× (477 kJ / mole CO₂)
= 132.5 watts. ↩
Again using the power of units:
(1 mole CO₂ / hour)
× (8 photons / CO₂ molecule)
× (1.8 eV / photon)
= 385.94 watts
So chloroplasts are at most ~34% (132.5 / 385.94) efficient at channeling the energy in light into photosynthesis. ↩
I find this 30% number amazingly low. (Well done, evolution.) And perhaps it should be somewhat lower. For one thing, the 30% figure comes from sunlight filtered to the 400-700 nm range. If you’ve got pure 680 nm light, absorption should be somewhat higher. Also, if photons are absorbed by some part of the plant other than the chloroplasts, they become heat and the energy is gone. But if they’re reflected or go through the plant, then they might go on to hit some other plant (provided you have a lot of plants around). If you really have pure 680 nm light and you have very densely packed plants, maybe you could drop this to 10-20%. ↩
Wikipedia quotes a 35-45% loss just for respiration in the leaf itself. But then this paper shows numbers ranging from 30% to 56% depending on the species and growth rate. ↩
I’ve estimated an overall efficiency of 132.5 watts / 918 watts ≈ 14.4%. If you go to Wikipedia, it estimates that ideal leaf efficiency with sunlight is only around 5.4%. That’s because sunlight contains a wide band of wavelengths and my calculation assumed an ideal 680 nm source. Around 47% falls outside the 400-700 nm range, and inside that range, around 24% is lost due to higher-energy photons with energy that gets wasted as heat. If you account for that, my estimate becomes 14.4% × (1-0.47) × (1-0.24) = 5.8%, which is close enough for government work. ↩
A traditional “60 watt” incandescent lightbulb is rated based on the power input. But only around 2% of that energy is actually converted to light. So 918 watts of pure red light isn’t what you get from 918 / 60 = 15.3 lightbulbs. It’s what you get from 918 / 60 / .02 = 765 lightbulbs. That said, your eyes aren’t very sensitive to 680 nm light, so the perceived lux wouldn’t be nearly so bad. ↩
The saturation point of plants is usually given in units of 300 μmol/m²/s. That the number of photons (in micromoles) that can be absorbed, per square meter of leaf, per second. A typical value for a shade-tolerant houseplant would be ~300 μmol/m²/s. If we assume again that the light is 680 nm so that each photon carries 1.8 eV of energy, then ~300 μmol of photons carries 51.92 joules. That’s 51.92 joules of energy per square meter of leaf surface, i.e. 52 watts. ↩
